{"id":"W7133283955","doi":"","title":"Updated Lake Chubsucker RPA 2011-2020","year":2023,"lang":"en","type":"other","venue":"Federal Open Science Repository of Canada / Le Dépôt fédéral de science ouverte du Canada","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Fisheries and Oceans Canada","keywords":"Marsh; Population; Hydrology (agriculture); Habitat; Tributary; Wetland; Wildlife; Spring (device)","routes":{"ca_aff":false,"ca_fund":true,"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":[0.00208432,0.001306805,0.000638963,0.006886448,0.001909209,0.002809565,0.002505462,0.001007078,0.03924916],"category_scores_gemma":[0.005228457,0.0006567718,0.0009594008,0.005861239,0.0003589956,0.001591885,0.002700218,0.001380012,0.01406642],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02164932,"about_ca_system_score_gemma":0.05487627,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9542339,"about_ca_topic_score_gemma":0.9590532,"domain_scores_codex":[0.9969065,0.0001010638,0.0001483782,0.0001435564,0.002240391,0.0004600486],"domain_scores_gemma":[0.9904408,0.0000923415,0.0002611231,0.0001120746,0.008425415,0.0006681507],"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":[0.0000888166,0.00003592758,0.006667929,0.0005185223,0.00004120142,0.00007992591,0.0001326438,0.001005409,0.0002288249,0.001147158,0.925212,0.06484156],"study_design_scores_gemma":[0.00002991766,0.00003359251,0.05229341,0.0004485504,0.00004829007,0.0000774372,0.0003739385,0.001022225,0.0003114315,0.0006822267,0.9446176,0.00006135603],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"other","genre_scores_codex":[0.009356988,0.004356924,0.003583346,0.005503618,0.001389522,0.000961807,0.7570334,0.002943313,0.214871],"genre_scores_gemma":[0.09155151,0.006651745,0.02023174,0.004485793,0.0002874341,0.002209059,0.641361,0.0007456534,0.2324761],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.04576612,"threshold_uncertainty_score":0.1570776,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008550941139139389,"score_gpt":0.2318969567936226,"score_spread":0.2233460156544832,"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."}}