{"id":"W4247455435","doi":"10.1515/iupac.88.0787","title":"Extrinsic Pathway","year":2017,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Effects and risks of endocrine disrupting chemicals","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canada Research Chairs; University of Toronto","funders":"","keywords":"Glossary; Terminology; Relation (database); Computer science; Linguistics; Data mining; Philosophy","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009703235,0.001579369,0.001313359,0.003581026,0.001175071,0.003737985,0.001797702,0.001638774,0.1233321],"category_scores_gemma":[0.008151929,0.0005754494,0.002337876,0.00538477,0.0004411425,0.00284415,0.002427842,0.001959484,0.09716811],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00150306,"about_ca_system_score_gemma":0.00360702,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01787117,"about_ca_topic_score_gemma":0.02885373,"domain_scores_codex":[0.9984119,0.0001942437,0.0003030078,0.0005853362,0.0003009062,0.0002046019],"domain_scores_gemma":[0.9969345,0.0009288064,0.0004432338,0.0007689153,0.00072417,0.0002003469],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0005002889,0.00004025818,0.007790509,0.005965813,0.0001814591,0.0001555143,0.0001034945,0.0005099149,0.0006207555,0.004649291,0.9496303,0.02985238],"study_design_scores_gemma":[0.00008669069,0.00001906973,0.005796458,0.001010509,0.00008146214,0.0001965593,0.00008080508,0.0001298941,0.0003081817,0.002518742,0.9897445,0.00002719604],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0004862441,0.0009379986,0.0003685271,0.0002059892,0.0001184312,0.00004664979,0.9905078,0.0003714423,0.006956923],"genre_scores_gemma":[0.001857843,0.001070966,0.0008691368,0.0004022136,0.00003210289,0.0001718688,0.9913251,0.0001379809,0.004132787],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1233321,"threshold_uncertainty_score":0.4125869,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01339148107875136,"score_gpt":0.4422300978095891,"score_spread":0.4288386167308377,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}