{"id":"W6886128752","doi":"10.15139/s3/saxvsf","title":"National Emission Inventory (NEI) 2016 modeling platform version 2","year":2021,"lang":"en","type":"dataset","venue":"UNC Dataverse","topic":"","field":"","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Download; Emission inventory; General partnership; Oil spill; Aviation; Fossil fuel","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":[0.0009630189,0.0006716523,0.0005507846,0.0007745018,0.000349687,0.0001537974,0.00119618,0.0007667594,0.01984461],"category_scores_gemma":[0.0009852282,0.0006811972,0.0002476057,0.0004796377,0.00009826106,0.00113168,0.001558122,0.00107853,0.1495681],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001577855,"about_ca_system_score_gemma":0.002253361,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005437538,"about_ca_topic_score_gemma":0.0001395031,"domain_scores_codex":[0.9950978,0.00011243,0.00067416,0.001164861,0.002323537,0.000627267],"domain_scores_gemma":[0.9968323,0.00009227866,0.0004360809,0.001710085,0.0005240235,0.0004052471],"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":[0.0001550494,0.0001990411,0.000001407223,0.0001743484,0.0001185377,0.0001687806,0.00001690499,0.001587304,0.0001804986,0.00001919544,0.9973378,0.00004109758],"study_design_scores_gemma":[0.001194055,0.00002646184,2.978838e-7,0.0008348814,0.0001899616,0.00003080455,0.0001501307,0.02742547,0.00005378415,0.0001908358,0.9691848,0.0007185157],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.000122295,0.00006878057,0.00003543992,0.000009178803,0.001462301,0.0002875917,0.9970257,0.0001430253,0.0008457058],"genre_scores_gemma":[0.000008395617,0.0003399111,0.0002914171,0.0002487106,0.000790843,0.0000168503,0.9969428,0.00012033,0.001240795],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1297235,"threshold_uncertainty_score":0.9995639,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04655707275754491,"score_gpt":0.2865000922005605,"score_spread":0.2399430194430156,"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."}}