{"id":"W4239607098","doi":"10.1515/iupac.87.0627","title":"Stimulus","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canada Research Chairs; University of Toronto","funders":"","keywords":"Glossary; Relation (database); Psychology; 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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001981168,0.001544965,0.001154994,0.002331646,0.0009114532,0.002989865,0.002634474,0.002128792,0.2695702],"category_scores_gemma":[0.01739649,0.000512016,0.001374,0.004156963,0.0004865241,0.002628076,0.002128442,0.001840011,0.2294503],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00198795,"about_ca_system_score_gemma":0.002897722,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01595653,"about_ca_topic_score_gemma":0.0294507,"domain_scores_codex":[0.9975667,0.000489013,0.0003764119,0.0007156804,0.0004977697,0.0003544801],"domain_scores_gemma":[0.9937649,0.002110033,0.0004817242,0.001270731,0.001955785,0.0004168838],"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":[0.0001742318,0.00002392016,0.001137228,0.0006262513,0.00001391875,0.00001977679,0.0000248383,0.0001352944,0.00004219508,0.0007479285,0.992394,0.004660481],"study_design_scores_gemma":[0.0003352392,0.00003565888,0.00381654,0.0005814445,0.00002063789,0.00007923401,0.000191394,0.0003134006,0.0002077701,0.002159239,0.9922255,0.00003399451],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.000228132,0.00007497182,0.0001112575,0.0001979518,0.00007664133,0.00008239024,0.995666,0.0003029267,0.003259671],"genre_scores_gemma":[0.001130902,0.00008887293,0.0005600424,0.0003657477,0.00003570057,0.0005481119,0.9932824,0.0001151228,0.003873016],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.7304298,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01706727320701345,"score_gpt":0.4239353375558777,"score_spread":0.4068680643488642,"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."}}