{"id":"W4252214206","doi":"10.1515/iupac.87.0623","title":"Stenosis","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Cancer and biochemical research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canada Research Chairs; University of Toronto","funders":"","keywords":"Glossary; Relation (database); Chemical nomenclature; Computer science; Psychology; Engineering ethics; Epistemology; Chemistry; Linguistics; Philosophy; Engineering; Data mining; Organic chemistry","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":[0.001648051,0.001483919,0.00144602,0.003844581,0.00101505,0.00405891,0.00245588,0.001851225,0.2616591],"category_scores_gemma":[0.01440425,0.0005775749,0.001753601,0.005595874,0.0004132363,0.002938843,0.002424093,0.001673752,0.2849276],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001724504,"about_ca_system_score_gemma":0.003255671,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0122926,"about_ca_topic_score_gemma":0.02021334,"domain_scores_codex":[0.9973527,0.0004051635,0.0004949819,0.0009272428,0.0005227563,0.0002971074],"domain_scores_gemma":[0.9944932,0.001319825,0.0005333537,0.001382527,0.001898602,0.0003724746],"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":[0.0001207182,0.00001461347,0.001249889,0.0009080744,0.00002763403,0.00002303178,0.000021386,0.00009019415,0.00007938999,0.0009450589,0.9886128,0.007907287],"study_design_scores_gemma":[0.0001240123,0.00001358481,0.002306356,0.0005079265,0.00002232171,0.00006548333,0.00006263737,0.0001365892,0.0001721148,0.001385579,0.9951859,0.00001754752],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001553913,0.0001587743,0.0001684536,0.000190326,0.00008594428,0.00004905554,0.9944549,0.0006406238,0.004096496],"genre_scores_gemma":[0.000563242,0.0001671075,0.0005586012,0.0003154364,0.00003164296,0.0001668982,0.9943507,0.0001914505,0.003654887],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.2616591,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01442251416303802,"score_gpt":0.4285630716528484,"score_spread":0.4141405574898104,"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."}}