{"id":"W2980224233","doi":"10.1111/gcb.14862","title":"Temperature change as a driver of spatial patterns and long‐term trends in chironomid (Insecta: Diptera) diversity","year":2019,"lang":"en","type":"article","venue":"Global Change Biology","topic":"Geology and Paleoclimatology Research","field":"Earth and Planetary Sciences","cited_by":82,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University; Dalhousie University","funders":"Russian Science Foundation; Deutsche Forschungsgemeinschaft; York University; National Science Foundation","keywords":"Subfossil; Chironomidae; Ecology; Biodiversity; Ecosystem; Alpha diversity; Wetland; Holocene; Climate change; Environmental science; Physical geography; Geography; Biology; Larva","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"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":[0.0001329912,0.0001411868,0.0002881394,0.0001311661,0.00007399877,0.000006097201,0.0002097038,0.0003196003,0.002151041],"category_scores_gemma":[0.000006836001,0.0001166618,0.00004486376,0.0001250074,0.0001975588,0.0001055466,0.0001433784,0.000177957,0.0001326518],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000003421202,"about_ca_system_score_gemma":0.00001007779,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.02008313,"about_ca_topic_score_gemma":0.09656987,"domain_scores_codex":[0.9989195,0.0001687739,0.0001247171,0.0003350494,0.00006498012,0.0003869826],"domain_scores_gemma":[0.9996489,0.00004291219,0.0000566122,0.0001471715,0.00001756684,0.00008682365],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001780733,0.00001878504,0.9895973,0.0000248684,0.00001877956,0.00003585877,0.000415658,8.649464e-8,0.000004433787,0.0000290914,0.000004133923,0.00967295],"study_design_scores_gemma":[0.0006372242,0.0004680026,0.9985486,0.00001351824,0.000007549846,0.00004141881,0.00002177411,0.00002572239,0.000004301387,0.00007573267,0.00004064013,0.0001155086],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9967412,0.001088745,3.947794e-7,0.0003472352,0.0004222332,0.0002040136,0.000358338,0.00001122275,0.0008266664],"genre_scores_gemma":[0.9988628,0.0002669631,0.000004877001,0.000300493,0.0001152388,0.000003276649,0.0004074508,0.000001218531,0.00003769994],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07648674,"threshold_uncertainty_score":0.9987611,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03388361292589141,"score_gpt":0.2612428397128091,"score_spread":0.2273592267869178,"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."}}