{"id":"W7034582089","doi":"","title":"USMCA Not A Win For America!","year":2019,"lang":"en","type":"other","venue":"Bulletin of Miscellaneous Information (Royal Gardens Kew)","topic":"Hydrological Forecasting Using AI","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Compromise; Sovereignty; Copying; Silver bullet; Government (linguistics)","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":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0001864886,0.0003074341,0.0004145358,0.00003355859,0.0000560454,0.00003218625,0.0004037713,0.0003651271,0.5327145],"category_scores_gemma":[0.0002044732,0.0002796707,0.0001788648,0.000008961109,0.0002533519,1.499376e-7,0.0001673024,0.0001971288,0.07705253],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008089846,"about_ca_system_score_gemma":0.000009603187,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004645318,"about_ca_topic_score_gemma":0.0002991923,"domain_scores_codex":[0.9984476,0.0000449501,0.0004659417,0.0002775156,0.0003973915,0.0003666257],"domain_scores_gemma":[0.9988153,0.0001432045,0.0005296612,0.0003859916,0.00001985063,0.0001059938],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000081009,0.00003186821,0.000003549457,0.0001390171,0.00002112763,0.000002873563,0.00005121771,0.004864924,0.000001728582,0.000004648071,0.9911301,0.003667921],"study_design_scores_gemma":[0.0003725303,0.000317977,0.000006830968,0.00009156232,0.00003406457,0.00001765193,0.000008552786,0.0004414351,0.0000081628,0.000008423005,0.9983737,0.0003191138],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.0001540624,0.00002388937,0.000004009791,0.0002472023,0.0002542762,0.0007046099,0.0001603014,0.0001771241,0.9982745],"genre_scores_gemma":[0.0008458785,0.00002285212,0.005472769,0.0009982226,0.00009472034,0.00002633421,0.00009371551,0.0001206798,0.9923248],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.455662,"threshold_uncertainty_score":0.9999655,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008282294880687808,"score_gpt":0.1895182454264135,"score_spread":0.1812359505457257,"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."}}