{"id":"W3017485611","doi":"","title":"Identification of reliable gridded reference data for statistical downscaling methods in Alberta","year":2017,"lang":"en","type":"article","venue":"AGUFM","topic":"Climate change and permafrost","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Identification (biology); Downscaling; Computer science; Remote sensing; Geology; Meteorology; Geography; Precipitation","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":[],"consensus_categories":[],"category_scores_codex":[0.000776881,0.00005597339,0.0001290345,0.00002916804,0.0001241248,0.00006871423,0.0005182332,0.00004529483,0.0007793311],"category_scores_gemma":[0.000610707,0.0000475947,0.00001152769,0.00003204462,0.00005635785,0.0002722912,0.0000358166,0.00005401498,0.00004521176],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000001528308,"about_ca_system_score_gemma":0.00001923906,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.0555224,"about_ca_topic_score_gemma":0.107752,"domain_scores_codex":[0.9992859,0.00003382175,0.0002336393,0.0002205203,0.00007777021,0.0001483857],"domain_scores_gemma":[0.9985525,0.0005202385,0.0001367101,0.0007241062,0.00002756682,0.00003886189],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002733204,0.00007462454,0.8336203,0.0003598835,0.00002951701,0.000008228331,0.0008658823,0.0004801997,0.01860866,0.002679758,0.006293724,0.1367059],"study_design_scores_gemma":[0.0005032644,0.00006498282,0.726669,0.00005912658,0.00003127486,0.00000339502,0.0001446976,0.2414906,0.002873784,0.00544404,0.02251518,0.0002006744],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8965493,0.0008472067,0.02584659,0.002669635,0.002782245,0.00129803,0.04736653,0.00003524332,0.02260522],"genre_scores_gemma":[0.9724172,0.0001633213,0.01717352,0.0000535327,0.00008178651,0.000002939688,0.009619409,0.000003448367,0.0004848793],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2410104,"threshold_uncertainty_score":0.950767,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2018237880462727,"score_gpt":0.4124893477195572,"score_spread":0.2106655596732845,"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."}}