{"id":"W4393781911","doi":"10.5281/zenodo.7306284","title":"Wood Buffalo Environmental Association (WBEA) Historical Monitoring Data used in \"Passive Tracer Modelling at Super-Resolution with WRF-ARW to Assess Mass-Balance Schemes\"","year":2022,"lang":"en","type":"dataset","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Remote Sensing and LiDAR Applications","field":"Environmental Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University; Environment and Climate Change Canada","funders":"","keywords":"TRACER; Weather Research and Forecasting Model; Environmental science; Association (psychology); Meteorology; Geography; Physics","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":[0.001036873,0.001501273,0.0009795299,0.001947175,0.0007036338,0.001383062,0.002318997,0.001524863,0.02183429],"category_scores_gemma":[0.002563393,0.0006558191,0.0009464045,0.004053982,0.0003760984,0.001164039,0.001208737,0.001694554,0.03373682],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001599931,"about_ca_system_score_gemma":0.002007497,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.07410677,"about_ca_topic_score_gemma":0.1035375,"domain_scores_codex":[0.9993572,0.00007971125,0.00005861535,0.0001842138,0.000225887,0.00009443728],"domain_scores_gemma":[0.9987608,0.0001904043,0.0001299299,0.0002872942,0.0005145287,0.0001169624],"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":[0.00004678999,0.00003959836,0.002101948,0.0003576628,0.00004430654,0.00003190082,0.00003759118,0.001217698,0.000264465,0.0006822921,0.9927497,0.002426041],"study_design_scores_gemma":[0.0002024069,0.00001238831,0.01273589,0.0002076543,0.00002771326,0.00004124966,0.0001315181,0.002493101,0.0009035641,0.001159969,0.9820336,0.00005106863],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0003177449,0.00002136006,0.0001270431,0.0000386925,0.0000163582,0.000008753746,0.998555,0.000296237,0.0006187542],"genre_scores_gemma":[0.0007928059,0.00002067984,0.000453748,0.0000162174,0.000003158227,0.00005082336,0.9980898,0.0000692652,0.0005034402],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.9258932,"threshold_uncertainty_score":0.1473508,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05883782141232995,"score_gpt":0.2532173555730462,"score_spread":0.1943795341607162,"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."}}