{"id":"W2523163744","doi":"10.1186/s12992-016-0192-6","title":"‘Manage and mitigate punitive regulatory measures, enhance the corporate image, influence public policy’: industry efforts to shape understanding of tobacco-attributable deforestation","year":2016,"lang":"en","type":"article","venue":"Globalization and Health","topic":"Smoking Behavior and Cessation","field":"Medicine","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"National Institutes of Health; National Cancer Institute; Tobacco-Related Disease Research Program","keywords":"Deforestation (computer science); Cultivation of tobacco; Tobacco industry; Agriculture; Punitive damages; Business; Political science; Economic growth; Development economics; Public economics; Geography; Economics","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":["sts"],"consensus_categories":[],"category_scores_codex":[0.01515045,0.0003702147,0.0002702386,0.00197638,0.007992269,0.009687589,0.001564059,0.005190397,0.003958771],"category_scores_gemma":[0.01680497,0.000346066,0.0003264165,0.002787185,0.01656805,0.008755688,0.005814899,0.007355227,0.0005057385],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01291262,"about_ca_system_score_gemma":0.01986296,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01177932,"about_ca_topic_score_gemma":0.01819679,"domain_scores_codex":[0.9909196,0.006419523,0.0002817614,0.0004088586,0.00112109,0.0008491167],"domain_scores_gemma":[0.9834078,0.0125166,0.001447987,0.000501495,0.001426668,0.0006993554],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.00004344029,0.0001380694,0.008105342,0.001867316,0.00003406784,0.001692887,0.6180539,0.0004796748,0.001803466,0.2159909,0.0318812,0.1199098],"study_design_scores_gemma":[0.00001516678,0.0001127656,0.01538675,0.004203809,0.00002924559,0.0005494885,0.3962383,0.0008952509,0.00167645,0.03244504,0.5483936,0.00005399862],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.2511111,0.02712547,0.01193757,0.5217378,0.001068468,0.0002383152,0.0001604393,0.0001005331,0.1865203],"genre_scores_gemma":[0.9540367,0.01285894,0.004144596,0.01958268,0.0002541869,0.000118121,0.00005659184,0.00004821947,0.008899997],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9920077,"threshold_uncertainty_score":0.09368801,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0910487133082282,"score_gpt":0.3464572383216047,"score_spread":0.2554085250133765,"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."}}