{"id":"W7071058515","doi":"","title":"RES and Cowessess First Nation to Accelerate Renewable Energy Goals in Saskatchewan","year":2021,"lang":"en","type":"other","venue":"","topic":"Machine Learning in Bioinformatics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Renewable energy; First nation; Energy (signal processing); Feed-in tariff; Sustainability; Energy consumption","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009747759,0.0006152394,0.0002430857,0.0006803238,0.002074582,0.003016598,0.0009272428,0.001944131,0.07524285],"category_scores_gemma":[0.001262975,0.0003019699,0.0004448311,0.0004880306,0.0006430434,0.0006085432,0.002457209,0.002251236,0.01970667],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007131476,"about_ca_system_score_gemma":0.04822333,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.4428726,"about_ca_topic_score_gemma":0.7972538,"domain_scores_codex":[0.9995031,0.00004602936,0.000006716116,0.00005268849,0.000198183,0.0001933194],"domain_scores_gemma":[0.9983482,0.0000967001,0.00002698056,0.00009136734,0.0005252139,0.0009115103],"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":[0.0001885149,0.0003963211,0.006292705,0.00006624239,0.00002461697,0.000601328,0.00009359937,0.0008058812,0.002481668,0.01401394,0.897945,0.07709025],"study_design_scores_gemma":[0.00006733763,0.00005086873,0.01205632,0.00006873447,0.00001110958,0.00008089467,0.000342921,0.001059824,0.002064722,0.002629976,0.9815441,0.00002319776],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.04093745,0.001924374,0.003564916,0.059886,0.005162819,0.0003544365,0.01671258,0.002775645,0.8686818],"genre_scores_gemma":[0.02406163,0.0006367528,0.002867402,0.006565884,0.00008078836,0.00008141624,0.002113537,0.000190284,0.9634025],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.5571274,"threshold_uncertainty_score":0.8805896,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01276258716735632,"score_gpt":0.2512869767297847,"score_spread":0.2385243895624284,"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."}}