{"id":"W2137744185","doi":"10.1111/j.1523-1739.2007.00767.x","title":"Edge Effects in the Great Tit: Analyses of Long‐term Data with GIS Techniques","year":2007,"lang":"en","type":"article","venue":"Conservation Biology","topic":"Avian ecology and behavior","field":"Environmental Science","cited_by":40,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke","funders":"Biotechnology and Biological Sciences Research Council","keywords":"Woodland; Avian clutch size; Ecology; Predation; Habitat; Nest (protein structural motif); Reproductive success; Geography; Reproduction; Biology; Parus; Demography; Population","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":[],"consensus_categories":[],"category_scores_codex":[0.0004214913,0.00005802262,0.00009505667,0.00003340652,0.00003508802,0.00000231102,0.0003120028,0.00008372935,0.000246326],"category_scores_gemma":[0.00004468214,0.00003433811,0.00000950775,0.0001905278,0.0003943862,0.00008197303,0.0000928102,0.00006791967,0.00002127467],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001881006,"about_ca_system_score_gemma":0.000007322217,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000173281,"about_ca_topic_score_gemma":0.003503561,"domain_scores_codex":[0.9994758,0.00008296231,0.0001287583,0.0001594491,0.0000391461,0.0001138326],"domain_scores_gemma":[0.9993848,0.0002075096,0.00007183531,0.000317326,0.000005737459,0.00001277697],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002096592,0.00003976419,0.9772083,0.000003258285,0.000003426187,0.00001182213,0.0000441717,1.792787e-7,0.01272424,0.00002846967,0.0003413318,0.009574059],"study_design_scores_gemma":[0.0001129633,0.0001351413,0.9855973,0.000005942995,0.0000170386,0.00001163165,0.00001012854,0.000004000808,0.01350636,0.00006256506,0.0004927733,0.000044155],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9956166,0.0000223972,0.003000328,0.0003357774,0.00002291728,0.0001875439,0.000005901428,0.00001272006,0.0007958715],"genre_scores_gemma":[0.9980101,0.000006218537,0.001043079,0.0007838337,0.000009754256,0.000009358005,0.0000750409,0.00000247519,0.00006012916],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009529904,"threshold_uncertainty_score":0.2697097,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06660044920656276,"score_gpt":0.3523965490013856,"score_spread":0.2857960997948228,"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."}}