{"id":"W1992482989","doi":"10.1177/107554702237846","title":"GM Food Labeling","year":2002,"lang":"en","type":"article","venue":"Science Communication","topic":"Genetically Modified Organisms Research","field":"Agricultural and Biological Sciences","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Food labeling; Balance (ability); Battle; State (computer science); Business; Matching (statistics); Law and economics; Marketing; Political science; Economics; Psychology","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":[0.001717669,0.0005745553,0.0002806,0.001709677,0.001561674,0.001611772,0.0008525236,0.00391268,0.04287114],"category_scores_gemma":[0.00419201,0.0002820357,0.0004324641,0.001254827,0.001608516,0.001469875,0.001733314,0.002350507,0.01825354],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0011573,"about_ca_system_score_gemma":0.0009456339,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001047123,"about_ca_topic_score_gemma":0.001560324,"domain_scores_codex":[0.9977705,0.0004528716,0.00007245135,0.0002440013,0.001325237,0.0001348948],"domain_scores_gemma":[0.9982488,0.0004607092,0.0002657466,0.0004127792,0.0004829101,0.0001290997],"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":[0.0002350996,0.0001384501,0.0007468486,0.0008971011,0.00002358356,0.0008686681,0.0009950267,0.0006636352,0.09601719,0.28294,0.2664654,0.3500091],"study_design_scores_gemma":[0.000006833041,0.00004087679,0.0003169935,0.00009318437,0.000007101946,0.0004660252,0.00004525093,0.00009382767,0.00929701,0.008741903,0.9808818,0.000009256759],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.007805541,0.007423138,0.02587496,0.01382835,0.00404444,0.000254119,0.001501559,0.00163952,0.9376284],"genre_scores_gemma":[0.1279296,0.01560642,0.08537534,0.02876516,0.002222831,0.0006872208,0.00455023,0.0008334442,0.7340297],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.04287114,"threshold_uncertainty_score":0.1434183,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08022664889241672,"score_gpt":0.2487940272561625,"score_spread":0.1685673783637458,"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."}}