{"id":"W2153423075","doi":"10.1136/tc.2005.013854","title":"Every document and picture tells a story: using internal corporate document reviews, semiotics, and content analysis to assess tobacco advertising","year":2006,"lang":"en","type":"article","venue":"Tobacco Control","topic":"Media Studies and Communication","field":"Social Sciences","cited_by":70,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"National Cancer Institute; Flight Attendant Medical Research Institute","keywords":"Tobacco industry; Semiotics; Advertising; Content analysis; Promotion (chess); Computer science; Sociology; Business; Political science; Linguistics; Social science","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":[],"consensus_categories":[],"category_scores_codex":[0.02640146,0.0004575514,0.0004178793,0.01418705,0.003559203,0.008741764,0.0006056215,0.0007821036,0.0007581301],"category_scores_gemma":[0.07784516,0.0003943976,0.0002815118,0.007306118,0.006469813,0.006862007,0.003312266,0.0009983348,0.0003298649],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003675897,"about_ca_system_score_gemma":0.003964789,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003025593,"about_ca_topic_score_gemma":0.005611253,"domain_scores_codex":[0.9528919,0.03850639,0.001675179,0.001000187,0.005410924,0.0005153348],"domain_scores_gemma":[0.8261485,0.1411441,0.01166667,0.005060846,0.01475701,0.001222973],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.0002682845,0.0001119516,0.03851525,0.001032845,0.00007859152,0.0005936867,0.7246532,0.0002643614,0.004904144,0.02440182,0.003204403,0.2019713],"study_design_scores_gemma":[0.00006154239,0.0005339247,0.07950658,0.002281167,0.0002442655,0.002321041,0.7230171,0.003727653,0.01953217,0.02866041,0.1398614,0.000252652],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8874992,0.006077992,0.03789572,0.002876738,0.0002119005,0.0007612477,0.0003238306,0.0001771697,0.06417619],"genre_scores_gemma":[0.9543433,0.002076454,0.03870707,0.0003211918,0.0001209894,0.0008380206,0.0002438344,0.00009738854,0.003251738],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02640146,"threshold_uncertainty_score":0.1396259,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06676342098341588,"score_gpt":0.321541658656726,"score_spread":0.2547782376733101,"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."}}