{"id":"W3121846677","doi":"","title":"The Structure of Argumentation in Health Product Messages","year":2010,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Discourse Analysis in Language Studies","field":"Arts and Humanities","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"","keywords":"Argumentation theory; Argument (complex analysis); Product (mathematics); Computer science; Health communication; Inference; Health informatics; Argumentation framework; Frame (networking); Data science; Epistemology; Psychology; Artificial intelligence; Health care; Medicine; Political science; Communication; Mathematics; Telecommunications","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":[0.01562516,0.0007820864,0.0006667811,0.00938906,0.004688008,0.01232313,0.001506358,0.003285181,0.004002226],"category_scores_gemma":[0.06131085,0.0007708795,0.0008146352,0.004914235,0.01152147,0.01521183,0.00438139,0.002264164,0.0005929747],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004872529,"about_ca_system_score_gemma":0.002683564,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001870074,"about_ca_topic_score_gemma":0.001153024,"domain_scores_codex":[0.9667652,0.02596885,0.001457342,0.001267735,0.003783367,0.000757637],"domain_scores_gemma":[0.903881,0.08377434,0.005409975,0.002443432,0.003811344,0.0006799712],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"qualitative","study_design_scores_codex":[0.0003901176,0.0001041552,0.004735595,0.0007854951,0.00006191376,0.001098426,0.3052053,0.002527762,0.005030856,0.6192582,0.001479548,0.05932254],"study_design_scores_gemma":[0.0001912415,0.0003041154,0.0120891,0.001839428,0.0001388609,0.001148338,0.1120094,0.02694692,0.007633111,0.7213655,0.1161647,0.0001692594],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5821085,0.004884818,0.2524543,0.00928466,0.0003336064,0.0007603617,0.0004647186,0.0004807272,0.1492282],"genre_scores_gemma":[0.9561765,0.000451457,0.03944579,0.0001218914,0.00005716149,0.0001995494,0.0002151815,0.0000798076,0.003252668],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01562516,"threshold_uncertainty_score":0.08263475,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006699042883549331,"score_gpt":0.2676018134467115,"score_spread":0.2609027705631621,"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."}}