{"id":"W4242103071","doi":"10.1515/iupac.85.0767","title":"Thomson","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta; National Research Council Canada","funders":"","keywords":"Terminology; Chemical nomenclature; Mass spectrometry; Chemistry; Standardization; Accelerator mass spectrometry; Analytical Chemistry (journal); Political science; Environmental chemistry; Chromatography; Law; Linguistics; 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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001650126,0.001680247,0.001573896,0.006788074,0.001308517,0.005914867,0.002486663,0.001719516,0.2571867],"category_scores_gemma":[0.0180742,0.0006892525,0.001601708,0.01311117,0.0004434963,0.004730553,0.003407556,0.001949274,0.403819],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00218302,"about_ca_system_score_gemma":0.00423304,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01694061,"about_ca_topic_score_gemma":0.02491825,"domain_scores_codex":[0.9966313,0.0004994067,0.0005124342,0.0009971194,0.0009993803,0.0003602656],"domain_scores_gemma":[0.9916728,0.001945462,0.0007794428,0.002084461,0.003112542,0.0004053648],"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":[0.00004404074,0.000007337456,0.000582544,0.0006631594,0.0000177012,0.00001228762,0.00002619318,0.00008246441,0.00005343255,0.001213759,0.9883054,0.008991626],"study_design_scores_gemma":[0.00002645316,0.000004510426,0.001009285,0.0003687909,0.000009468556,0.00002243503,0.00004407062,0.00006527935,0.000089799,0.001446985,0.9969009,0.00001199284],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00007779044,0.000180428,0.0001966739,0.0002176954,0.00005897083,0.00001871693,0.9939554,0.0007963902,0.004497953],"genre_scores_gemma":[0.0003263798,0.0003254505,0.0005725977,0.0001875021,0.00002398517,0.00008276079,0.9940971,0.000315284,0.004068927],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.7428133,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01745895096813537,"score_gpt":0.4335355664735262,"score_spread":0.4160766155053908,"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."}}