{"id":"W3107302366","doi":"10.1111/oik.07685","title":"Large‐scale multi‐trophic co‐response models and environmental control of pelagic food webs in Québec lakes","year":2020,"lang":"en","type":"article","venue":"Oikos","topic":"Isotope Analysis in Ecology","field":"Environmental Science","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"GDG Environnement; Environment and Climate Change Canada","funders":"","keywords":"Trophic level; Ecology; Food web; Phytoplankton; Pelagic zone; Ecological niche; Zooplankton; Niche; Biology; Interspecific competition; Species richness; Environmental science; Habitat; Nutrient","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002494304,0.0001300677,0.0002702391,0.00003848687,0.00005017243,0.000007255499,0.0001882011,0.00007846835,0.001834805],"category_scores_gemma":[0.00004918702,0.0001261993,0.00005912948,0.0001032239,0.0002501696,0.0001408246,0.000133829,0.0001307073,0.0002026093],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001118513,"about_ca_system_score_gemma":0.00001518034,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001658857,"about_ca_topic_score_gemma":0.006478766,"domain_scores_codex":[0.9987889,0.0002002785,0.0002555462,0.0003171901,0.0001821911,0.0002559177],"domain_scores_gemma":[0.9995192,0.0001139948,0.00008243266,0.0001818093,0.00000147118,0.0001011031],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0006400074,0.0004127866,0.900683,0.000009456754,0.00004609342,0.00003158961,0.00664204,0.01939446,0.07159101,0.00002255968,0.0002209714,0.0003060208],"study_design_scores_gemma":[0.005770117,0.000906726,0.3760989,0.000008283967,0.00008050615,0.00001318766,0.002661298,0.6063057,0.003822875,0.000151811,0.003753066,0.0004275502],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.997045,0.0001600911,0.001335859,0.0008199776,0.00001227356,0.0002093934,0.00006892142,0.00001254935,0.0003358986],"genre_scores_gemma":[0.998729,0.00002639603,0.000289861,0.00071146,0.00001033188,0.00002190431,0.000005182269,0.00001392224,0.0001919551],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5869112,"threshold_uncertainty_score":0.9990777,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009389683648761952,"score_gpt":0.2071733131984889,"score_spread":0.197783629549727,"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."}}