{"id":"W2731445504","doi":"","title":"Soft Targets: Nurses and the Pharmaceutical Industry","year":2009,"lang":"en","type":"article","venue":"Aporia","topic":"Biotechnology and Related Fields","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Pharmaceutical industry; Business; Medicine","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004855215,0.000717081,0.0004658077,0.001412806,0.005188344,0.01607335,0.0009736987,0.012356,0.04641673],"category_scores_gemma":[0.01349678,0.0002369364,0.000263402,0.001261908,0.01234955,0.01033439,0.006614018,0.009199772,0.005466111],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007014452,"about_ca_system_score_gemma":0.008926064,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00358521,"about_ca_topic_score_gemma":0.007466462,"domain_scores_codex":[0.9966847,0.001656661,0.00009744444,0.0002084814,0.000956897,0.0003957296],"domain_scores_gemma":[0.983631,0.009855037,0.001445899,0.0004698981,0.001677769,0.002920367],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00009294757,0.0002114009,0.001655453,0.000533217,0.00001601685,0.0004734423,0.004705953,0.0002960526,0.0003070327,0.53208,0.3225441,0.1370844],"study_design_scores_gemma":[0.0000367322,0.0001009492,0.001635538,0.001236722,0.000009189357,0.0003185229,0.01198095,0.0004176194,0.0002722086,0.3309452,0.6530076,0.0000387411],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.00768108,0.05346105,0.001386798,0.6545492,0.008719414,0.00002564982,0.00003207032,0.00005792821,0.2740868],"genre_scores_gemma":[0.3412863,0.07427344,0.001604664,0.2702222,0.02257203,0.0001315612,0.00005085309,0.00009997543,0.2897589],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.04641673,"threshold_uncertainty_score":0.1552795,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01216544730550216,"score_gpt":0.3053697889753272,"score_spread":0.293204341669825,"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."}}