{"id":"W4408098383","doi":"10.22541/au.174103422.22336230/v1","title":"Trait clustering offers expanded insight into crustacean zooplankton metacommunity structuring processes in boreal lakes","year":2025,"lang":"en","type":"preprint","venue":"","topic":"Fish Ecology and Management Studies","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"Metacommunity; Zooplankton; Crustacean; Boreal; Structuring; Ecology; Environmental science; Trait; Geography; Oceanography; Biology; Geology; Economics; Computer science; Demography","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000427726,0.0002491745,0.0002511188,0.001640896,0.0005935056,0.0005528782,0.0001661633,0.0001830495,0.0005949538],"category_scores_gemma":[0.001058584,0.0001493234,0.0002998532,0.00108121,0.0002900922,0.0003116558,0.0003740027,0.0001676657,0.00006600945],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005710043,"about_ca_system_score_gemma":0.0004329366,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.08062328,"about_ca_topic_score_gemma":0.1708333,"domain_scores_codex":[0.9997573,0.00005716591,0.00001815294,0.00008339887,0.00004017516,0.00004376809],"domain_scores_gemma":[0.9993089,0.0001809363,0.0002412036,0.00006879181,0.0001157324,0.00008432785],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00008108262,0.00002075213,0.9547212,0.0000471636,0.0001668597,0.00005172187,0.0009664997,0.0009540352,0.02498026,0.0001674113,0.0001706893,0.0176724],"study_design_scores_gemma":[6.196171e-7,0.000008351003,0.9983875,0.000002619783,0.000008501325,0.00002667664,0.0001418785,0.001135722,0.0001382149,0.00005562413,0.00009060482,0.000003778745],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9975376,0.0001940203,0.001537281,0.00002637243,0.000001291504,0.00000507864,0.0002377123,0.00002602564,0.0004346301],"genre_scores_gemma":[0.9986761,0.00003225098,0.0009837801,0.000008374396,0.000002660812,0.000003234078,0.0001894982,0.00000454476,0.00009955094],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08062328,"threshold_uncertainty_score":0.160308,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01753822963750174,"score_gpt":0.2514049068488795,"score_spread":0.2338666772113778,"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."}}