{"id":"W2765813394","doi":"10.1002/fes3.124","title":"Six years old and growing strongly","year":2017,"lang":"en","type":"article","venue":"Food and Energy Security","topic":"Genetically Modified Organisms Research","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"China; Political science; Quarter (Canadian coin); Population; Public relations; Library science; Sociology; Geography; Law; Computer science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.004290295,0.001063419,0.0009519889,0.00165986,0.008503351,0.009596903,0.001815091,0.003342416,0.1032015],"category_scores_gemma":[0.01045744,0.0005087105,0.0006623561,0.001340101,0.005278171,0.00999502,0.007082053,0.01005398,0.09209105],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002976889,"about_ca_system_score_gemma":0.005378284,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004903905,"about_ca_topic_score_gemma":0.008452814,"domain_scores_codex":[0.9956999,0.0009423927,0.0002017593,0.001025803,0.001407698,0.0007224025],"domain_scores_gemma":[0.9924521,0.0006651499,0.0003057795,0.0005071581,0.003094762,0.002975034],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.0000692434,0.00007844967,0.00143142,0.0001477118,0.00001452508,0.0005015507,0.006348,0.00003009336,0.0004418081,0.03633665,0.8748323,0.07976809],"study_design_scores_gemma":[0.000001793529,0.00001444091,0.0002384591,0.00006771571,0.000001599435,0.0001747305,0.0009895338,0.00001072134,0.0000448455,0.001331878,0.9971162,0.000008079339],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.01247883,0.03456785,0.005639066,0.3927283,0.0817696,0.0002060822,0.001658823,0.001003748,0.4699478],"genre_scores_gemma":[0.02690543,0.01048868,0.002476088,0.08496188,0.006913624,0.0001127112,0.0006972738,0.0004836055,0.8669607],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.1032015,"threshold_uncertainty_score":0.3452435,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02094006151666729,"score_gpt":0.2259944674926995,"score_spread":0.2050544059760323,"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."}}