def get_additional(bwo, **kwargs):
"""Return formatted data of object."""
from inspire.modules.predicter.utils import get_classification_from_task_results
keywords = get_classification_from_task_results(bwo)
results = bwo.get_tasks_results()
prediction_results = results.get("arxiv_guessing", {})
if prediction_results:
prediction_results = prediction_results[0].get("result")
return render_template(
'workflows/styles/harvesting_record_additional.html',
object=bwo,
keywords=keywords,
score=prediction_results.get("max_score"),
decision=prediction_results.get("decision")
)
def _filter_core_keywords(obj, eng):
from inspire.utils.knowledge import check_keys
from inspire.modules.predicter.utils import (
get_classification_from_task_results,
update_classification_in_task_results,
)
result = get_classification_from_task_results(obj)
if result is None:
return
filtered_core_keywords = {}
for core_keyword, times_counted in result.get("Core keywords").items():
if not check_keys(filter_kb, [core_keyword]):
filtered_core_keywords[core_keyword] = times_counted
result["Filtered Core keywords"] = filtered_core_keywords
update_classification_in_task_results(obj, result)
def is_record_relevant(obj, *args, **kwargs):
"""Shall we halt this workflow for potential acceptance or just reject?"""
from inspire.modules.predicter.utils import (
get_classification_from_task_results,
)
results = obj.get_tasks_results()
prediction_results = results.get("arxiv_guessing", {})
classification_results = get_classification_from_task_results(obj)
if prediction_results and classification_results:
prediction_results = prediction_results[0].get("result")
score = prediction_results.get("max_score")
decision = prediction_results.get("decision")
core_keywords = classification_results.get("Core keywords")
if decision.lower() == "rejected" and score > 0 and \
len(core_keywords) == 0:
return False
return True