{"id":"W4244223000","doi":"10.1515/iupac.87.0567","title":"Rebound","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Consumer behavior in food and health","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canada Research Chairs; University of Toronto","funders":"","keywords":"Glossary; Chemical nomenclature; Relation (database); Computer science; Chemistry; Linguistics; Philosophy; 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":[0.001520579,0.0002771953,0.0004722051,0.0001728539,0.00074287,0.0001303274,0.0006448066,0.000513087,0.0118955],"category_scores_gemma":[0.0006598943,0.0002273472,0.0001576746,0.0002122382,0.0005519807,0.00009921822,0.0001171852,0.0004972219,0.00001222516],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000905612,"about_ca_system_score_gemma":0.004943955,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.007459943,"about_ca_topic_score_gemma":0.1013056,"domain_scores_codex":[0.9965955,0.0002544395,0.0004049141,0.0004504725,0.001621328,0.0006733322],"domain_scores_gemma":[0.99811,0.0001510775,0.0002346395,0.0006500625,0.0004841467,0.0003700712],"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":[0.00003084218,0.0000966423,0.00003642615,0.00003809389,0.00002051634,0.00002773794,0.0001604413,4.148346e-9,4.451438e-7,0.0001851568,0.9769666,0.02243714],"study_design_scores_gemma":[0.0003161445,0.00006737092,0.00005789628,0.0002219434,0.00008061671,0.00000152936,0.0002034926,1.425074e-8,4.469413e-7,0.0004026402,0.9983371,0.0003108318],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00009785227,0.0009470278,0.00000525652,0.003609384,0.002194962,0.0003364237,0.9918453,0.00010493,0.0008588356],"genre_scores_gemma":[0.00002335192,0.004949914,0.00001693392,0.0003364126,0.002184855,0.00001335585,0.9895161,0.00002428671,0.002934781],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.09384561,"threshold_uncertainty_score":0.9991494,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04816177735754922,"score_gpt":0.5128897829485365,"score_spread":0.4647280055909873,"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."}}