{"id":"W4233038656","doi":"10.1515/iupac.88.1201","title":"Pituitary","year":2017,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Academic Writing and Publishing","field":"Arts and Humanities","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":[],"consensus_categories":[],"category_scores_codex":[0.001239006,0.001462206,0.001209229,0.003548507,0.001005531,0.003589277,0.002319132,0.001613037,0.2375476],"category_scores_gemma":[0.012662,0.0005541632,0.001515848,0.006226575,0.0004435289,0.002920342,0.002507748,0.001631493,0.2830397],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001595767,"about_ca_system_score_gemma":0.002702005,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01822732,"about_ca_topic_score_gemma":0.03053439,"domain_scores_codex":[0.9978245,0.0003438266,0.0003979986,0.0007223916,0.0004704353,0.0002407925],"domain_scores_gemma":[0.9953275,0.001124488,0.0004595281,0.001134996,0.001668314,0.0002850773],"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":[0.00008215688,0.00001295332,0.001208604,0.0008555051,0.0000212727,0.00002005482,0.00003518143,0.00008681436,0.00007550983,0.0009400694,0.987895,0.008766911],"study_design_scores_gemma":[0.00006213786,0.00001029331,0.002874085,0.000533997,0.00001593949,0.00005704925,0.0001097092,0.0001018409,0.0001245798,0.001293317,0.9947973,0.00001967437],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.000166367,0.0001875397,0.0001685747,0.000179408,0.0000842833,0.00003497514,0.9941368,0.0003513888,0.004690656],"genre_scores_gemma":[0.0006491397,0.0002075115,0.0004561009,0.0002577144,0.00002770645,0.0001542346,0.9943748,0.0001164147,0.003756383],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.2375476,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03526978863830414,"score_gpt":0.4055045889910499,"score_spread":0.3702348003527458,"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."}}