{"id":"W4251625579","doi":"10.1086/688286","title":"Commentary","year":2016,"lang":"en","type":"article","venue":"Journal of the Association for Consumer Research","topic":"","field":"","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Kellogg's (Canada)","funders":"","keywords":"Generosity; Download; Library science; Consumer research; Altmetrics; Political science; Computer science; Advertising; Law; Business; World Wide Web","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":[0.01163349,0.00006465054,0.0001654462,0.0002293728,0.0002464577,0.00005896144,0.0006272457,0.00006802153,0.0001361204],"category_scores_gemma":[0.006258394,0.00003123947,0.0002571332,0.000352004,0.00009054532,0.0002665413,0.0001157309,0.000341199,0.000954056],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001961593,"about_ca_system_score_gemma":0.0001519941,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001529206,"about_ca_topic_score_gemma":0.00002451441,"domain_scores_codex":[0.9966498,0.0009377081,0.0004115647,0.00007984835,0.001525561,0.0003954986],"domain_scores_gemma":[0.9935364,0.003298185,0.0006953633,0.0002304729,0.002145352,0.00009419728],"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":[0.0001450433,0.00006268649,0.1818723,0.000003459963,0.0002133426,5.201359e-7,0.00006409655,4.132498e-7,0.01556443,0.0003390033,0.8005841,0.001150654],"study_design_scores_gemma":[0.002615747,0.0001107525,0.03941978,0.00009317619,0.00004863603,0.000009107354,0.00007832179,0.000005080599,0.01051094,0.005169664,0.9418709,0.00006791849],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6140299,0.0007675792,0.0001029138,0.3785497,0.001802519,0.001201198,0.0002569131,0.00006129577,0.003227982],"genre_scores_gemma":[0.9884922,0.00004401998,0.0001708242,0.0004874746,0.0003349135,0.00001356497,5.155896e-7,0.00008966556,0.01036682],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3780622,"threshold_uncertainty_score":0.9998238,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09792781574425348,"score_gpt":0.413359747568262,"score_spread":0.3154319318240085,"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."}}