{"id":"W4393615464","doi":"10.5281/zenodo.3540954","title":"Global Fire Weather Indices - DMC using default DC start-up","year":2019,"lang":"en","type":"dataset","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Disaster Management and Resilience","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta; Natural Resources Canada; Canadian Forest Service; University of British Columbia","funders":"","keywords":"Environmental science; Meteorology; Climatology; Geography; Geology","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":[0.0006425961,0.00126424,0.001019837,0.002757178,0.0009877406,0.001605737,0.00202783,0.000834899,0.01521744],"category_scores_gemma":[0.002816889,0.0004300634,0.001089496,0.005449724,0.0002889974,0.0008922428,0.0009832479,0.001675587,0.01551831],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003998487,"about_ca_system_score_gemma":0.006732571,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.7324784,"about_ca_topic_score_gemma":0.8011717,"domain_scores_codex":[0.9993292,0.0000427511,0.00004946995,0.0001726313,0.000249353,0.000156619],"domain_scores_gemma":[0.9978006,0.00008424837,0.0001183093,0.0003051825,0.001537197,0.0001543703],"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":[0.0001301459,0.00004468358,0.02363931,0.0004003892,0.0001350786,0.0000798043,0.0001026288,0.006514224,0.0005353217,0.001466113,0.9544134,0.01253896],"study_design_scores_gemma":[0.0001700685,0.0000151991,0.07410277,0.0002900996,0.00006492955,0.0000701899,0.000206287,0.009806341,0.001368646,0.001293713,0.9124926,0.000119168],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.001785537,0.00006429642,0.0003728524,0.0000448466,0.00004694387,0.00003195581,0.9950747,0.000643513,0.001935408],"genre_scores_gemma":[0.004495068,0.00005067031,0.001220037,0.00003010721,0.00001063767,0.00007769103,0.9932042,0.0001476764,0.0007638788],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.7324784,"threshold_uncertainty_score":0.5381942,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06129822127903499,"score_gpt":0.3166934199450782,"score_spread":0.2553951986660432,"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."}}