{"id":"W4254967044","doi":"10.1515/iupac.88.1236","title":"Primitive Groove","year":2017,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"History and advancements in chemistry","field":"Chemistry","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":[0.001334266,0.001793275,0.001514179,0.004260931,0.001295585,0.005093984,0.003147984,0.002077069,0.2625771],"category_scores_gemma":[0.01218125,0.0008456171,0.001958902,0.006830942,0.0005569331,0.004339581,0.00410992,0.002207661,0.3839286],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001519823,"about_ca_system_score_gemma":0.003047899,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01687224,"about_ca_topic_score_gemma":0.03361328,"domain_scores_codex":[0.9980849,0.0003039034,0.0003273958,0.0006238946,0.0004121859,0.0002477264],"domain_scores_gemma":[0.9955614,0.001171784,0.0003694943,0.00140343,0.00120047,0.0002935397],"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":[0.00006849456,0.000009952246,0.000618398,0.0008806612,0.00001694687,0.00001709872,0.00003439547,0.00008130656,0.00007867076,0.001120106,0.9905486,0.006525439],"study_design_scores_gemma":[0.00004550816,0.000006589261,0.001042448,0.0003262674,0.000008816137,0.00003157316,0.00005612042,0.00009353532,0.0001029884,0.001324691,0.9969489,0.00001263274],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0000925524,0.0001173301,0.0001993592,0.0001550606,0.00006200432,0.00002953163,0.993944,0.001157961,0.004242204],"genre_scores_gemma":[0.0003982275,0.0001698619,0.0005885946,0.0002090257,0.00001749891,0.0001045674,0.9955818,0.0003406131,0.002589945],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.2625771,"threshold_uncertainty_score":0.8784078,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01843098069724916,"score_gpt":0.4266250298323044,"score_spread":0.4081940491350552,"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."}}