{"id":"W6948375714","doi":"10.5063/f1fx77p9","title":"Mines in Alaska with subsetting by watershed and SASAP region, 2010 to 2016","year":2018,"lang":"en","type":"dataset","venue":"UC Santa Barbara","topic":"Photovoltaic Systems and Sustainability","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Watershed; Footprint; Hydrology (agriculture); Surface mining; Water resources; Commission","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004931041,0.0004036508,0.0004737103,0.00009061829,0.000119452,0.0000749946,0.000450858,0.0002685569,0.0005534489],"category_scores_gemma":[0.00009819273,0.0002925948,0.00003845831,0.0002635157,0.0003280753,0.0001873371,0.000382805,0.0002084182,0.0001804381],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002941722,"about_ca_system_score_gemma":0.00003967238,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03134391,"about_ca_topic_score_gemma":0.01214552,"domain_scores_codex":[0.9976038,0.0001200444,0.0004105342,0.0009108964,0.0003622223,0.000592532],"domain_scores_gemma":[0.9986953,0.00007009099,0.0001391831,0.000825338,0.00001896299,0.0002511887],"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":[0.00006302605,0.00004429375,0.06098432,0.00007875352,0.000008853391,0.0000611885,0.0001990122,0.00000116294,0.0004037674,2.608913e-8,0.9380311,0.0001245076],"study_design_scores_gemma":[0.0003642133,0.0001552814,0.02576528,0.0001405884,0.00001920936,0.00004859756,0.0002153217,0.000007601187,0.0002154042,0.00001939979,0.9726006,0.0004485405],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"dataset","genre_scores_codex":[0.5399429,0.0002384915,0.000007213693,0.0004072994,0.0003176825,0.00127266,0.4575658,0.00003732651,0.0002106896],"genre_scores_gemma":[0.06922422,0.0003573796,0.000343995,0.002311693,0.0006496319,0.0005001952,0.9171529,0.0001460947,0.009313852],"genre_candidate":"dataset","genre_consensus":null,"teacher_disagreement_score":0.4707187,"threshold_uncertainty_score":0.9999526,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005762247341060732,"score_gpt":0.2103568399061608,"score_spread":0.2045945925651001,"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."}}