{"id":"W1965578243","doi":"10.1111/j.1600-0633.2004.00069.x","title":"Quantifying the effectiveness of regional habitat quality index models for predicting densities of juvenile Atlantic salmon (<i>Salmo salar</i> L.)","year":2004,"lang":"en","type":"article","venue":"Ecology Of Freshwater Fish","topic":"Fish Ecology and Management Studies","field":"Environmental Science","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ministère des Ressources naturelles et des Forêts; Institut National de la Recherche Scientifique; Université Laval","funders":"","keywords":"Salmo; Habitat; Juvenile; Fishery; Environmental science; Index (typography); Ecology; Geography; Fish <Actinopterygii>; Biology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001662642,0.0001398664,0.0004597513,0.00004689329,0.0001824069,0.00000351741,0.0002750495,0.0001228096,0.00004703991],"category_scores_gemma":[0.0001414551,0.00010868,0.0001215786,0.00009167394,0.0009694798,0.0001594994,0.0002814964,0.0001066682,0.000002557904],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006638041,"about_ca_system_score_gemma":0.00001713823,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008245056,"about_ca_topic_score_gemma":0.04313832,"domain_scores_codex":[0.9985405,0.0002706234,0.0004748732,0.0002661933,0.0001708191,0.0002769622],"domain_scores_gemma":[0.9983034,0.001088483,0.0003233996,0.000225547,0.00003779117,0.00002142772],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002749658,0.0001574072,0.972147,0.0003324026,0.0001351061,0.000001908314,0.0008919161,0.02082146,0.001846163,0.001169983,0.002205514,0.00001617426],"study_design_scores_gemma":[0.001052414,0.0002764924,0.9761264,0.00005645201,0.00006302507,0.000003538275,0.0004381604,0.0007696733,0.008411851,0.01257601,0.0001145282,0.0001114742],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9964988,0.0000140077,0.001289806,0.0007596764,0.000168242,0.0005799288,0.00003966645,0.00001947541,0.0006304534],"genre_scores_gemma":[0.9988881,0.00001380889,0.0006765631,0.000241406,0.00001557511,0.00008975909,0.00001562188,0.0000112082,0.00004795636],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04231381,"threshold_uncertainty_score":0.9743219,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02890381823133303,"score_gpt":0.2575027456953259,"score_spread":0.2285989274639929,"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."}}