{"id":"W4317569322","doi":"10.1101/2023.01.19.524212","title":"Decomposing drivers in avian insectivory: large-scale effects of climate, habitat and bird diversity","year":2023,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Animal Vocal Communication and Behavior","field":"Biochemistry, Genetics and Molecular Biology","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke","funders":"Consejo Superior de Investigaciones Científicas; Fundação para a Ciência e a Tecnologia; Fondation BNP Paribas; Xunta de Galicia; Javna Agencija za Raziskovalno Dejavnost RS; BNP Paribas Cardif; Academy of Finland; Grantová Agentura České Republiky","keywords":"Insectivore; Ecology; Predation; Abundance (ecology); Habitat; Species richness; Biodiversity; Soundscape; Biology; Taxon; Geography; Sound (geography)","routes":{"ca_aff":true,"ca_fund":false,"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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003376149,0.0002846921,0.0003542897,0.0001722604,0.0001706269,0.00003623958,0.0004140471,0.0004488556,0.000002089934],"category_scores_gemma":[0.00009495484,0.0003288995,0.0001057161,0.0002149057,0.00014278,0.000009432353,0.002781522,0.0003799881,0.000008685737],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000632262,"about_ca_system_score_gemma":0.00009731999,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001304969,"about_ca_topic_score_gemma":0.0002753747,"domain_scores_codex":[0.9984744,0.0001573202,0.0002824634,0.0005948103,0.0001521245,0.0003388402],"domain_scores_gemma":[0.9987517,0.00003776286,0.0002095319,0.0007208548,0.0001476378,0.0001325097],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.00005138894,0.0001122122,0.480915,0.0002823597,0.00002725286,0.00001211676,0.00001903024,0.000003380678,0.5185408,0.00001563643,0.00001877504,0.000002033694],"study_design_scores_gemma":[0.0005435345,0.0001167463,0.8046361,0.0002437279,0.00005181167,1.200995e-8,0.00001194871,0.00004529171,0.1939111,8.584935e-7,0.0001354132,0.0003034055],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9983255,0.0005927792,0.0002360254,0.00004402785,0.0002416808,0.0003902197,0.00007402414,0.00009236296,0.000003438605],"genre_scores_gemma":[0.9969283,0.001444512,0.001404506,0.00006954715,0.00004596479,0.00003400627,0.000001226084,0.00007022181,0.000001722661],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3246297,"threshold_uncertainty_score":0.9999163,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01318678041470851,"score_gpt":0.2361784603924713,"score_spread":0.2229916799777628,"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."}}