{"id":"W4237264985","doi":"10.1515/iupac.79.1321","title":"Gene Expression","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Gene expression and cancer classification","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Glossary; Chemical nomenclature; Computer science; Multidisciplinary approach; Hazard; Toxicology; Chemistry; Biology; Linguistics; Philosophy; Sociology; Social science","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":[0.001485837,0.002669316,0.002752813,0.003646115,0.001224678,0.003272976,0.003836343,0.002665095,0.05461884],"category_scores_gemma":[0.005516118,0.0008489386,0.00268724,0.006248222,0.0005144452,0.001330403,0.001854115,0.002654667,0.09301198],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001764702,"about_ca_system_score_gemma":0.002884032,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0127774,"about_ca_topic_score_gemma":0.02648717,"domain_scores_codex":[0.9980037,0.0002557372,0.0002438378,0.0008268096,0.0004383065,0.0002316426],"domain_scores_gemma":[0.9983838,0.000466114,0.0001792659,0.0004900831,0.0003459642,0.0001348272],"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":[0.0003827267,0.00006902658,0.003784409,0.002943031,0.0002116536,0.0001001025,0.00005186979,0.001099751,0.001158398,0.0009558049,0.9777983,0.01144487],"study_design_scores_gemma":[0.0004521657,0.00007413865,0.008333861,0.0005771593,0.0002108677,0.0003008363,0.00007392854,0.001049294,0.001477466,0.002547671,0.9848247,0.00007782115],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0002816727,0.0003051536,0.0002438446,0.00007188345,0.00004472454,0.00002407351,0.9975957,0.0006704652,0.0007624324],"genre_scores_gemma":[0.0004620888,0.0001502744,0.0005677345,0.0000946922,0.000007792367,0.0001509155,0.9979036,0.00007871663,0.0005841072],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.05461884,"threshold_uncertainty_score":0.1827182,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01293370134187388,"score_gpt":0.3806280263808769,"score_spread":0.367694325039003,"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."}}