{"id":"W4242196231","doi":"10.1515/iupac.88.0386","title":"Abortion","year":2017,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Reproductive Health and Contraception","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canada Research Chairs; University of Toronto","funders":"","keywords":"Glossary; Terminology; Abortion; Relation (database); Computer science; Biology; Pregnancy; Linguistics; Philosophy; Genetics; Data mining","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0006135462,0.0002900557,0.0006518573,0.0001639122,0.0002056172,0.00004498901,0.0001591726,0.0003977741,0.001402274],"category_scores_gemma":[0.00131238,0.0002447974,0.0001603411,0.0000665906,0.0001188057,0.00008777088,0.00004338593,0.0007085744,0.00001192594],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003975616,"about_ca_system_score_gemma":0.001517989,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002444319,"about_ca_topic_score_gemma":0.0003794366,"domain_scores_codex":[0.9977154,0.00004512697,0.0004034978,0.0005659153,0.0009222184,0.0003478737],"domain_scores_gemma":[0.996976,0.00001581382,0.0004081585,0.001505474,0.0008433542,0.000251158],"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":[0.0007235818,0.0002537676,0.00008005037,0.0004746947,0.00006179522,0.00009644494,0.000005297999,2.019285e-7,0.00002025129,0.00000171588,0.9815843,0.01669787],"study_design_scores_gemma":[0.001285989,0.0005128139,0.005742977,0.0004595246,0.0002832808,0.00007631135,0.000009924111,0.000003808866,0.00001212648,0.00004731848,0.991363,0.0002029542],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0007842617,0.0016214,0.00005119649,0.00325569,0.001166372,0.0006793811,0.9922813,0.00005900826,0.0001014359],"genre_scores_gemma":[0.0001109472,0.002186486,0.00004315535,0.0005966516,0.004890359,0.00002590061,0.9910064,0.00002756328,0.001112511],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.01649492,"threshold_uncertainty_score":0.9995106,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02525933638754015,"score_gpt":0.4831295294089001,"score_spread":0.45787019302136,"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."}}