{"id":"W2886938444","doi":"10.31274/sciencecommunication-180809-86","title":"Analyzing GM Food Risk Arguments through an Online, Multi-media Case Study","year":2012,"lang":"en","type":"article","venue":"Iowa State University Summer Symposium on Science Communication","topic":"Genetically Modified Organisms Research","field":"Agricultural and Biological Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Winnipeg","funders":"Iowa State University","keywords":"Computer 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":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.001322616,0.000186581,0.0001671677,0.00009267655,0.001712054,0.0001599027,0.001708673,0.00006303025,0.00004609452],"category_scores_gemma":[0.0001057625,0.0001031563,0.00005484483,0.001435704,0.0005146951,0.001601142,0.0007469965,0.0003671191,0.0000531217],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002203187,"about_ca_system_score_gemma":0.00004207832,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006194519,"about_ca_topic_score_gemma":0.01348932,"domain_scores_codex":[0.9972771,0.0007724835,0.0002144777,0.0004843022,0.0006185487,0.0006331334],"domain_scores_gemma":[0.9982314,0.0003386579,0.0001558366,0.0005708392,0.0003009692,0.0004022772],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001330332,0.008624669,0.7348198,0.000005109042,0.00007194799,0.00008317487,0.03436025,0.0003012955,0.1730781,0.0004159523,0.00004909711,0.04805756],"study_design_scores_gemma":[0.0009200923,0.00141336,0.9110112,0.00001514863,0.00006347064,0.00003579916,0.07710909,0.001364934,0.005931662,0.00005344162,0.001548094,0.0005336734],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9984775,0.00004762735,0.0001086057,0.0003812765,0.00008436944,0.0004493367,0.0001197854,0.0000727314,0.0002587858],"genre_scores_gemma":[0.9972628,0.0003538076,0.002196925,0.0000499221,0.00002918531,0.000001623347,0.0000491453,0.000002258011,0.00005438118],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1761914,"threshold_uncertainty_score":0.9995876,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1263929631974965,"score_gpt":0.3139419589422369,"score_spread":0.1875489957447404,"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."}}