{"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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002388193,0.000313872,0.0003171723,0.00007656137,0.00006291224,0.00003579762,0.0005347682,0.0005383896,0.001693485],"category_scores_gemma":[0.0005197337,0.0002277088,0.000215689,0.00009789776,0.0001773737,0.000001561275,0.0004195305,0.0002754346,0.000003095984],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001286207,"about_ca_system_score_gemma":0.0008070958,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000763078,"about_ca_topic_score_gemma":0.0003087206,"domain_scores_codex":[0.9978399,0.00004866096,0.0002651699,0.0006067991,0.0007765754,0.0004629533],"domain_scores_gemma":[0.9984058,0.00001885901,0.00009111241,0.0008459002,0.0004210802,0.0002172156],"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":[0.0003908272,0.0001015576,0.000005251764,0.00007283942,0.0001031501,0.00001107455,5.827036e-7,6.676373e-8,0.01347304,6.395281e-7,0.9773668,0.008474167],"study_design_scores_gemma":[0.0006364828,0.0003643098,0.00001512646,0.00009764165,0.00003690954,0.000006183056,0.00000422436,1.223401e-7,0.02140653,0.00001998712,0.9770847,0.000327775],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0008987714,0.00142382,0.0000414324,0.0004337847,0.000282097,0.0001846813,0.9966276,0.00001115379,0.00009665069],"genre_scores_gemma":[0.0001470019,0.00531793,0.00001212026,0.0003902909,0.002005558,0.00002313029,0.9907942,0.00003239802,0.001277394],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.008146391,"threshold_uncertainty_score":0.9992191,"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."}}