{"id":"W6894288545","doi":"10.5683/sp3/8wsiza","title":"Replication Data and Code for: Manufacturing Output and Extreme Temperature: Evidence from Canada","year":2022,"lang":"en","type":"dataset","venue":"Borealis","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Replication (statistics); Download; Replicate; Confidentiality; Code (set theory); Data file; Data access; Table (database)","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002299036,0.001972152,0.001498669,0.007048107,0.00250321,0.004560283,0.003772826,0.001327671,0.1502177],"category_scores_gemma":[0.02537566,0.001343969,0.001926244,0.01785612,0.0008738085,0.001493191,0.002231022,0.002659984,0.08494811],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01027907,"about_ca_system_score_gemma":0.02907032,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8524259,"about_ca_topic_score_gemma":0.8873097,"domain_scores_codex":[0.9970149,0.0002948484,0.000331842,0.000583545,0.001104982,0.0006698535],"domain_scores_gemma":[0.9755027,0.002813957,0.001554052,0.004677866,0.01403811,0.001413318],"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":[0.00003522365,0.00001148002,0.001457225,0.000135921,0.0000222168,0.00001081395,0.00003004548,0.0002416845,0.00002241547,0.0003412463,0.9963653,0.001326368],"study_design_scores_gemma":[0.0004763678,0.000013996,0.02268792,0.000359873,0.0000626422,0.0000452469,0.0002954986,0.0005427454,0.0003970233,0.001111989,0.9739085,0.00009827841],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001438505,0.00001881197,0.0000790224,0.00007685726,0.00002796647,0.00004376109,0.9982627,0.0002990445,0.001048006],"genre_scores_gemma":[0.001039,0.00003763241,0.000454643,0.00005946467,0.00001160578,0.000286444,0.9952441,0.0002726187,0.002594463],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1502177,"threshold_uncertainty_score":0.5025281,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09892465549419883,"score_gpt":0.3008881585366673,"score_spread":0.2019635030424685,"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."}}