{"id":"W4248053512","doi":"10.1515/iupac.88.0986","title":"Limb Bud","year":2017,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"","field":"","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; Philosophy; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0009431136,0.001359952,0.001357351,0.003688918,0.001093216,0.003671966,0.002542045,0.001591153,0.180449],"category_scores_gemma":[0.008156808,0.0007065554,0.001586898,0.006364563,0.0003885872,0.002058364,0.002692279,0.001846677,0.219515],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001473465,"about_ca_system_score_gemma":0.002767984,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02412903,"about_ca_topic_score_gemma":0.04356457,"domain_scores_codex":[0.9986683,0.0002005066,0.0002539103,0.0003752997,0.0003194632,0.0001825066],"domain_scores_gemma":[0.9966246,0.0008747604,0.0003903662,0.0008803768,0.0009910366,0.0002388266],"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":[0.0001106029,0.00001034777,0.00131932,0.001259216,0.00003077153,0.0000289134,0.0000347135,0.0001583618,0.0001135029,0.001111427,0.9888353,0.006987616],"study_design_scores_gemma":[0.00008514335,0.00001134428,0.003435539,0.0007564318,0.00002065334,0.00007179306,0.00006889847,0.0001024682,0.0001323897,0.001199975,0.9940977,0.00001781265],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00009980785,0.0001201298,0.000092036,0.000078614,0.00003052217,0.00001375764,0.9973404,0.0002492783,0.001975501],"genre_scores_gemma":[0.0003480492,0.0001613939,0.0003026403,0.0001022938,0.000009797256,0.00006480555,0.9973724,0.00009323362,0.001545417],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.819551,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02499758915184488,"score_gpt":0.4687531436372315,"score_spread":0.4437555544853866,"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."}}