{"id":"W4414138273","doi":"10.1002/ece3.71908","title":"Habitat and Trophic Specialization Among Greenland Cod (<i>Gadus ogac</i>) Morphotypes in the Context of Climate Change Resilience","year":2025,"lang":"en","type":"article","venue":"Ecology and Evolution","topic":"Isotope Analysis in Ecology","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba; University of Windsor; Fisheries and Oceans Canada; University of Northern British Columbia","funders":"Fisheries and Oceans Canada; Canada Research Chairs; ArcticNet; Aurora Research Institute; Fisheries Joint Management Committee; Marine Environmental Observation Prediction and Response Network","keywords":"Generalist and specialist species; Trophic level; Arctic; Context (archaeology); Climate change; Habitat; Population; Resource (disambiguation); Food web","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":[0.0001585387,0.0001558908,0.0001431338,0.0007347115,0.0005144724,0.0004266001,0.0001632846,0.0001386369,0.0005054618],"category_scores_gemma":[0.0003108487,0.0001014604,0.0001439346,0.0005307548,0.0004710747,0.0001562145,0.0003759366,0.0001363193,0.00006037873],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008557001,"about_ca_system_score_gemma":0.0003881843,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1772589,"about_ca_topic_score_gemma":0.4915882,"domain_scores_codex":[0.9999001,0.00001138763,0.000006824473,0.00003634476,0.00001586137,0.00002956054],"domain_scores_gemma":[0.9997532,0.00001867096,0.0001000626,0.00001318554,0.00005398645,0.00006090236],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00006043318,0.000007708845,0.993462,0.000006529136,0.00003216271,0.00003442394,0.0003992355,0.00006199477,0.004707582,0.00002446273,0.00005440441,0.001149098],"study_design_scores_gemma":[2.402025e-7,0.000003710219,0.9996642,7.234553e-7,0.00000184733,0.000009909451,0.0002442728,0.00002246025,0.00002788921,0.000002637476,0.00002144278,6.369273e-7],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.999805,0.0000116525,0.00001435101,0.000002955461,4.756322e-7,8.341827e-7,0.00006653477,5.106035e-7,0.00009764227],"genre_scores_gemma":[0.9997928,0.000008908996,0.00004308074,0.000004776954,3.754027e-7,0.000001610382,0.00008670118,5.339946e-7,0.00006122804],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1772589,"threshold_uncertainty_score":0.3524543,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006247505602599646,"score_gpt":0.2165862334355188,"score_spread":0.2103387278329192,"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."}}