{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009179362,0.00006943953,0.00008504588,0.000004491887,0.0003346501,0.0001937791,0.0001765142,0.00006860354,0.00006073352],"category_scores_gemma":[0.00003437559,0.00003040637,0.00002022185,0.00002227119,0.0001135028,0.0001144361,0.0002373142,0.00007380707,0.000002723217],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000003697582,"about_ca_system_score_gemma":0.000002713069,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007890813,"about_ca_topic_score_gemma":0.001386842,"domain_scores_codex":[0.9993823,0.00002440985,0.00006220144,0.0002070263,0.0001205971,0.000203451],"domain_scores_gemma":[0.9997269,0.00003380416,0.00002294555,0.00006946391,0.00001714555,0.0001297265],"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":[0.00005759772,0.0001345032,0.0294146,0.00002142934,0.00006027469,0.00003045577,0.0003866677,0.000002059229,0.3652412,0.1041639,0.0006429863,0.4998444],"study_design_scores_gemma":[0.000196017,0.0005349441,0.9585423,0.000009672405,0.000006034428,0.0000076201,0.0001369307,0.00007457703,0.006304286,0.008715173,0.02528995,0.0001825218],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9970621,0.0002156808,5.93719e-7,0.0009126883,0.00004087291,0.00001716757,0.00001260652,0.00001677881,0.001721492],"genre_scores_gemma":[0.9994263,0.0001331114,0.00002916946,0.00006527189,0.0001423667,0.000002526557,0.000004865055,6.86401e-7,0.0001956935],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9291277,"threshold_uncertainty_score":0.2573892,"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."}}