{"id":"W247911794","doi":"","title":"Textual Analyses of Nutrition Messages on Prime Time Television.","year":2001,"lang":"en","type":"article","venue":"Canadian home economics journal","topic":"Culinary Culture and Tourism","field":"Agricultural and Biological Sciences","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Prime time; Prime (order theory); Advertising; Business; Computer science; Psychology; Mathematics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.0001468576,0.0001066611,0.0001978614,0.0000597113,0.0002102392,0.00008227229,0.0002020943,0.00008999222,0.002676785],"category_scores_gemma":[0.00001735095,0.00004699165,0.0001356622,0.0001366008,0.00003528697,0.0001498496,0.00001060853,0.0001551167,0.0001466432],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000116694,"about_ca_system_score_gemma":0.00005050586,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003189357,"about_ca_topic_score_gemma":0.01617089,"domain_scores_codex":[0.9992779,0.00003421046,0.0002508703,0.0001405078,0.00005502478,0.0002414526],"domain_scores_gemma":[0.9993382,0.00005827267,0.0001345694,0.00004451165,0.00005508143,0.0003694124],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003300016,0.001001749,0.01918305,0.00001822602,0.000521816,0.0007653786,0.0003091537,0.0008155496,0.1483967,0.002474573,0.2714804,0.5547034],"study_design_scores_gemma":[0.0008439196,0.001324221,0.2171427,0.0001174974,0.00006796461,0.001045101,0.0007379573,0.0002365746,0.005541422,0.004394062,0.7678885,0.0006600474],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9889011,0.0003929844,4.841326e-7,0.002939572,0.00007962879,0.00006659634,0.0000636163,0.00000712831,0.007548827],"genre_scores_gemma":[0.9964093,0.0008931246,0.00004392046,0.00030103,0.0008724766,0.000001434172,0.00004302444,0.000001201781,0.001434513],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5540434,"threshold_uncertainty_score":0.9982349,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02872744294437579,"score_gpt":0.2337261390369617,"score_spread":0.2049986960925859,"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."}}