{"id":"W7119534898","doi":"10.5061/dryad.g1jwstr47","title":"Data from: Differential impacts of human land use on native and non-native fish in mountain watersheds","year":2025,"lang":"en","type":"dataset","venue":"Open MIND","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Government of Alberta; University of Calgary","funders":"Forest Resource Improvement Association of Alberta; Mitacs","keywords":"Trout; Occupancy; Habitat; Ecosystem; Rainbow trout; Land use; Introduced species; Brown trout","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"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":[0.0005787801,0.0009101423,0.0006571562,0.00199688,0.0006601203,0.001298111,0.00163017,0.0009797432,0.01834013],"category_scores_gemma":[0.002992015,0.0004202482,0.0007846009,0.004255749,0.0003102423,0.0004527019,0.0009559395,0.000749107,0.01081155],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002601547,"about_ca_system_score_gemma":0.003640026,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.5929292,"about_ca_topic_score_gemma":0.7151479,"domain_scores_codex":[0.99962,0.0000374708,0.00003821189,0.00009918614,0.0001215845,0.00008357347],"domain_scores_gemma":[0.9988862,0.0002763774,0.0001470082,0.0001320378,0.0004334153,0.0001249504],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.0001312128,0.00004294378,0.0180544,0.001104692,0.0001311851,0.00009032199,0.0001471818,0.001940025,0.0001875297,0.0006962055,0.9722044,0.005270036],"study_design_scores_gemma":[0.0005361944,0.00003453189,0.1290424,0.0006391705,0.0001095948,0.0001204844,0.0005212416,0.002544514,0.0004341777,0.001070577,0.8648769,0.00007020657],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0009742347,0.00006853502,0.00003411447,0.00004152041,0.000006300518,0.00000571102,0.9983417,0.0000859935,0.0004418917],"genre_scores_gemma":[0.002070188,0.00004552999,0.0001571032,0.00001899245,0.000002640483,0.0000248844,0.9971703,0.00001499409,0.0004954158],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.5929292,"threshold_uncertainty_score":0.8189362,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08269184251691315,"score_gpt":0.3774794479443965,"score_spread":0.2947876054274834,"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."}}