{"id":"W4234366279","doi":"10.1515/iupac.88.0954","title":"Intramembrous Ossification","year":2017,"lang":"it","type":"dataset","venue":"IUPAC Standards Online","topic":"Heterotopic Ossification and Related Conditions","field":"Medicine","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":[0.001276549,0.001224086,0.001272549,0.006058478,0.0006504835,0.002178624,0.001541846,0.001217438,0.0577371],"category_scores_gemma":[0.01041205,0.000458053,0.001824785,0.005654279,0.0006194241,0.001466073,0.002032489,0.001504355,0.0317018],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009501518,"about_ca_system_score_gemma":0.002370132,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007663271,"about_ca_topic_score_gemma":0.0156346,"domain_scores_codex":[0.9983476,0.0002071305,0.000553165,0.0004017432,0.000347398,0.0001428781],"domain_scores_gemma":[0.9948989,0.001597986,0.00137402,0.001005201,0.0008604102,0.0002635552],"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":[0.0005471389,0.00003835295,0.01204675,0.01370022,0.0002153587,0.0002632213,0.0001096687,0.0004703798,0.0009055885,0.001933767,0.9232196,0.04654991],"study_design_scores_gemma":[0.0002543764,0.00005170238,0.03022891,0.005673841,0.0001671447,0.0009746503,0.0001702066,0.0002752436,0.0007277637,0.002352531,0.9590656,0.0000579951],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0008243315,0.001314968,0.0003268329,0.0001181668,0.00008912791,0.0000838593,0.9941877,0.0002365086,0.002818459],"genre_scores_gemma":[0.002740518,0.001378904,0.001353103,0.0002044716,0.00004705651,0.0003874208,0.9921116,0.00008688891,0.001690051],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.0577371,"threshold_uncertainty_score":0.1931498,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02906251534279866,"score_gpt":0.4585745650211328,"score_spread":0.4295120496783341,"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."}}