{"id":"W2541606687","doi":"10.1007/s10980-016-0456-9","title":"Using multiple metrics to estimate seasonal landscape connectivity for Blanding’s turtles (Emydoidea blandingii) in a fragmented landscape","year":2016,"lang":"en","type":"article","venue":"Landscape Ecology","topic":"Wildlife-Road Interactions and Conservation","field":"Environmental Science","cited_by":30,"is_retracted":false,"has_abstract":false,"ca_institutions":"Toronto Zoo; University of Toronto","funders":"","keywords":"Landscape connectivity; Landscape ecology; Ecology; Habitat; Resistance distance; Geography; Computer science; Biological dispersal; Biology","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0004669939,0.0002387383,0.0003481579,0.0002799287,0.0001862788,0.00004869985,0.0002193988,0.0001742238,0.002287117],"category_scores_gemma":[0.0007312153,0.0001790709,0.00009225013,0.0005868025,0.00004575047,0.0002866552,0.0001712015,0.0001136637,0.0002164577],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002352023,"about_ca_system_score_gemma":0.0000352494,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001869403,"about_ca_topic_score_gemma":0.005997599,"domain_scores_codex":[0.998224,0.00009504963,0.0003543622,0.0005475329,0.0001921543,0.000586886],"domain_scores_gemma":[0.9984133,0.00100509,0.0001513584,0.0002358625,0.00003358987,0.0001608491],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000237562,0.0001381772,0.9821576,0.000008538031,0.00002708395,0.000009172206,0.0001052838,0.001689695,0.004478148,0.00006004372,0.00900095,0.002087678],"study_design_scores_gemma":[0.002935809,0.0002671066,0.8070632,0.00004428915,0.00003526012,0.00003707841,0.0001030765,0.1800201,0.0005120204,0.000288835,0.008328317,0.0003648463],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9825604,0.00002058404,0.01370433,0.001246076,0.0005122856,0.0005463829,0.00008220924,0.0000697721,0.00125793],"genre_scores_gemma":[0.9954436,0.000009362086,0.003341418,0.000378389,0.0001222368,0.0001557571,0.00003573509,0.00002916773,0.0004842955],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1783304,"threshold_uncertainty_score":0.9986249,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02438246343191033,"score_gpt":0.2942147930052365,"score_spread":0.2698323295733262,"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."}}