{"id":"W4245492931","doi":"10.1002/div.3408","title":"Alberto‐Culver Co.","year":2006,"lang":"en","type":"article","venue":"Mergent s Dividend Achievers","topic":"Legal Cases and Commentary","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Beauty; Business; Cash; Supply chain; Product (mathematics); Marketing; Advertising; Art; Aesthetics; Finance; Mathematics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00008425077,0.0001587112,0.0001965664,0.00006510715,0.00009894918,0.00001904289,0.00008985399,0.00004514031,0.003320894],"category_scores_gemma":[0.00001169245,0.0001322983,0.0001902817,0.0001232581,0.00004289934,0.0001110821,0.00004741926,0.000153049,0.0005073147],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007974739,"about_ca_system_score_gemma":0.00002700365,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001886691,"about_ca_topic_score_gemma":0.00007301437,"domain_scores_codex":[0.9989,0.00002504032,0.0002135082,0.0002356339,0.0003363436,0.0002894489],"domain_scores_gemma":[0.9994892,0.00002642159,0.00004586648,0.0002783297,0.00002115449,0.0001390564],"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":[0.0001918947,0.0004884709,0.240622,0.00005557297,0.0001497494,0.0002937345,0.00009243398,0.00003412666,0.01357091,0.001407662,0.741302,0.001791502],"study_design_scores_gemma":[0.001901011,0.0001922271,0.199529,0.00004628038,0.0002318817,0.00008185091,0.0001017944,0.0000550898,0.0102451,0.0001426931,0.7871779,0.000295213],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9549563,0.0004566402,0.00008156188,0.007106321,0.0004434055,0.0002239244,0.00001801501,0.00008245903,0.03663135],"genre_scores_gemma":[0.9866424,0.00004456392,0.0001961453,0.003189975,0.0003914968,0.00001385053,0.0001665385,0.00002382504,0.009331209],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04587588,"threshold_uncertainty_score":0.9975902,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009578470194594917,"score_gpt":0.2623854870334553,"score_spread":0.2528070168388604,"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."}}