{"id":"W6948933565","doi":"10.5281/zenodo.1164286","title":"pacificclimate/ClimDown 1.0.4","year":2018,"lang":"en","type":"other","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Pacific Institute for Climate Solutions; Simon Fraser University","funders":"","keywords":"Downscaling; Selection (genetic algorithm); Work (physics); Process (computing)","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009346509,0.001627523,0.0009604819,0.00176605,0.0006713882,0.002941681,0.003062709,0.001001847,0.2092488],"category_scores_gemma":[0.002454238,0.001794698,0.001319209,0.003369236,0.0004061563,0.002837188,0.002092035,0.002950639,0.2261039],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005894557,"about_ca_system_score_gemma":0.001713792,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02620426,"about_ca_topic_score_gemma":0.02315415,"domain_scores_codex":[0.999656,0.00003121866,0.00002155648,0.00009332161,0.0001435154,0.0000544146],"domain_scores_gemma":[0.9991794,0.00006879299,0.0000567371,0.0003050417,0.0002315203,0.000158529],"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":[0.00007400622,0.00002050251,0.0007785305,0.0002661919,0.00004279281,0.00003104268,0.00005228534,0.001611771,0.0006123602,0.001671038,0.9743422,0.02049728],"study_design_scores_gemma":[0.0001469369,0.00001239616,0.002379248,0.00008002194,0.00002580676,0.00003706985,0.00002006422,0.005215066,0.003161194,0.003173907,0.9856884,0.00005984902],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"software","genre_scores_codex":[0.001878538,0.0002957029,0.02928333,0.000628188,0.0004610191,0.0002016413,0.6097649,0.2627227,0.09476397],"genre_scores_gemma":[0.01644186,0.0006034654,0.05216985,0.0005037564,0.0002086595,0.0005704153,0.5767767,0.3063796,0.04634558],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.2092488,"threshold_uncertainty_score":0.7000069,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0366307485789393,"score_gpt":0.2558329492169091,"score_spread":0.2192022006379698,"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."}}