{"id":"W4221099532","doi":"10.14573/altex.2012022","title":"The use of categorical regression in evidence integration","year":2022,"lang":"en","type":"review","venue":"ALTEX","topic":"Environmental and Social Impact Assessments","field":"Environmental Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University; University of Ottawa","funders":"","keywords":"Categorical variable; Regression; Regression analysis; Statistics; Risk assessment; Computer science; Risk analysis (engineering); Econometrics; Data mining; Environmental health; Medicine; Mathematics","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0003228869,0.0001670365,0.000394181,0.00002422431,0.0001499783,0.00002670837,0.0003446229,0.0000855623,0.001129462],"category_scores_gemma":[0.000152342,0.00009427046,0.0001490372,0.0003095507,0.00015157,0.0002332046,0.0003907318,0.0003474143,0.00009695801],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007392515,"about_ca_system_score_gemma":0.00002503613,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001122729,"about_ca_topic_score_gemma":0.0002064048,"domain_scores_codex":[0.9984249,0.0003889208,0.0003869835,0.0002191804,0.0004002495,0.0001797884],"domain_scores_gemma":[0.998727,0.0006806048,0.0002741903,0.0002721432,7.465675e-7,0.00004527948],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000003003154,0.00004149197,0.0002964023,0.00008511625,0.00000526044,0.000004045593,0.0001018169,0.000008005274,0.000002645769,0.00003859679,0.001379038,0.9980346],"study_design_scores_gemma":[0.00003247357,0.00004295006,0.0007464841,0.0007236489,0.00003738332,0.000003040542,0.00004432355,0.00001871301,0.000001562815,0.00007844706,0.9981664,0.0001045487],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0002368013,0.9982961,0.00001231896,0.00003642356,0.0002146505,0.0004749073,0.000005608451,0.000007193869,0.0007160036],"genre_scores_gemma":[0.0006599316,0.9980558,0.00005246676,0.00002365075,0.00001755746,0.00007705348,0.00001936752,0.00001440518,0.00107978],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.99793,"threshold_uncertainty_score":0.9997836,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.250025676201112,"score_gpt":0.409626615504204,"score_spread":0.159600939303092,"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."}}