{"id":"W2030170053","doi":"10.1080/19462166.2010.486481","title":"The structure of argumentation in health product messages","year":2010,"lang":"en","type":"article","venue":"Argument & Computation","topic":"Multi-Agent Systems and Negotiation","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"","keywords":"Argumentation theory; Product (mathematics); Computer science; Mathematics; Linguistics; Philosophy","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005397412,0.00009147757,0.0001185405,0.00009342923,0.0001454874,0.00008793038,0.0002618374,0.00002156242,0.000004528696],"category_scores_gemma":[0.00003158291,0.00006828891,0.00002682818,0.0002799102,0.00002186657,0.0003456964,0.00004675197,0.0001206924,0.000004791044],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004578902,"about_ca_system_score_gemma":0.0000643371,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002518725,"about_ca_topic_score_gemma":0.0004838142,"domain_scores_codex":[0.9987128,0.0001347087,0.0004415986,0.0002419973,0.0003044754,0.0001643998],"domain_scores_gemma":[0.9991735,0.0000939559,0.0003735524,0.0002501269,0.00007436925,0.00003456169],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.00002882149,0.000347779,0.04870835,0.000284639,0.00005734975,0.000002268442,0.0118928,0.02403527,0.2151209,0.1516961,0.001634415,0.5461913],"study_design_scores_gemma":[0.001562159,0.0001785577,0.5828178,0.0001026769,0.000005587971,0.00001103585,0.0002268511,0.3346979,0.06099522,0.01641729,0.002664616,0.0003203273],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8643826,0.0001282952,0.1306229,0.002945363,0.001158171,0.0006566317,0.000002044724,0.00004807728,0.00005588572],"genre_scores_gemma":[0.9896189,0.00001938024,0.01017751,0.00007599616,0.00004956239,0.000006203418,0.00001475172,0.000004918079,0.0000327669],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.545871,"threshold_uncertainty_score":0.2784741,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01080003608730033,"score_gpt":0.2800755219068811,"score_spread":0.2692754858195807,"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."}}