{"id":"W2092894192","doi":"10.4296/cwrj3603869","title":"Development of a National Fish Passage Database for Canada (CanFishPass): Rationale, Approach, Utility, and Potential Applicability to Other Regions","year":2011,"lang":"en","type":"article","venue":"Canadian Water Resources Journal / Revue canadienne des ressources hydriques","topic":"Fish Ecology and Management Studies","field":"Environmental Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Government of Canada; Fisheries and Oceans Canada; Carleton University","funders":"","keywords":"Hydropower; Fish <Actinopterygii>; Database; Resource (disambiguation); Flood control; Computer science; Upstream (networking); Environmental resource management; Construction engineering; Flood myth; Engineering; Environmental science; Geography; Fishery","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.006693026,0.0009143868,0.0009552517,0.02065521,0.002704117,0.004688631,0.004618468,0.001151911,0.02318756],"category_scores_gemma":[0.02779493,0.0005526678,0.0007890618,0.02689683,0.000726546,0.004043489,0.003005067,0.001137047,0.01209038],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01440418,"about_ca_system_score_gemma":0.07081777,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.897316,"about_ca_topic_score_gemma":0.9092187,"domain_scores_codex":[0.9967681,0.0002380955,0.0006002561,0.000367911,0.001759772,0.0002658253],"domain_scores_gemma":[0.9509923,0.004745898,0.001859583,0.00322792,0.03565799,0.003516291],"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":[0.0003327682,0.0001708677,0.02318022,0.003662013,0.00009929945,0.0004534895,0.001688391,0.002436675,0.002471399,0.01250686,0.7067989,0.2461991],"study_design_scores_gemma":[0.00007650838,0.0000533411,0.0303729,0.001868608,0.000117973,0.000203082,0.0014564,0.004101605,0.002259162,0.001108534,0.9581981,0.0001836319],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"methods","genre_scores_codex":[0.01651361,0.00141618,0.02894822,0.003313138,0.0002087036,0.003582975,0.8842487,0.008988187,0.05278026],"genre_scores_gemma":[0.02575891,0.002077078,0.1080376,0.0005892385,0.00004195402,0.001795943,0.8458152,0.0013685,0.01451557],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.102684,"threshold_uncertainty_score":0.2065774,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02959922624190527,"score_gpt":0.1980257623495995,"score_spread":0.1684265361076942,"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."}}