{"id":"W3022578821","doi":"10.1016/j.actao.2020.103577","title":"The influence of matrix type in the relationship between patch size and amphibia richness: A global Meta-Analysis","year":2020,"lang":"en","type":"article","venue":"Acta Oecologica","topic":"Amphibian and Reptile Biology","field":"Environmental Science","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Conselho Nacional de Desenvolvimento Científico e Tecnológico; Coordenação de Aperfeiçoamento de Pessoal de Nível Superior; Carleton University","keywords":"Species richness; Ecology; Meta-analysis; Habitat; Context (archaeology); Habitat fragmentation; Landscape ecology; Fragmentation (computing); Affect (linguistics); Biology; Geography; Psychology; Medicine","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008644141,0.002291964,0.003748023,0.002561775,0.001166472,0.002459388,0.002439348,0.001808701,0.00491341],"category_scores_gemma":[0.008379752,0.001335307,0.01729178,0.003458133,0.001559556,0.00194082,0.00239109,0.002089073,0.0003958194],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004858963,"about_ca_system_score_gemma":0.0008913564,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01426466,"about_ca_topic_score_gemma":0.02169376,"domain_scores_codex":[0.9946736,0.002689274,0.0003701413,0.001642133,0.0002014088,0.0004234423],"domain_scores_gemma":[0.9888374,0.007987278,0.0006385134,0.001600866,0.0003918546,0.0005441229],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"meta_analysis","study_design_scores_codex":[0.002452369,0.0001245416,0.5857795,0.0027709,0.3860516,0.0007583589,0.0005922936,0.004260604,0.004367087,0.0006725751,0.0009124788,0.01125775],"study_design_scores_gemma":[0.000471111,0.001056465,0.660252,0.0005991078,0.3139851,0.0009174906,0.001351895,0.01598023,0.001012428,0.002131476,0.002053623,0.0001891091],"study_design_candidate":"meta_analysis","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9379549,0.04622974,0.01112994,0.0008067163,0.0003069572,0.00005598108,0.002130511,0.0002908641,0.001094376],"genre_scores_gemma":[0.9965363,0.001123643,0.001615644,0.0001280686,0.00003335753,0.0000263388,0.0002858233,0.00005473816,0.0001960811],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01426466,"threshold_uncertainty_score":0.04571515,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05975055766475687,"score_gpt":0.2993941337845555,"score_spread":0.2396435761197986,"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."}}