{"id":"W2088142504","doi":"10.1016/j.foreco.2013.07.033","title":"Quantifying connectivity using graph based connectivity response curves in complex landscapes under simulated forest management scenarios","year":2013,"lang":"en","type":"article","venue":"Forest Ecology and Management","topic":"Wildlife-Road Interactions and Conservation","field":"Environmental Science","cited_by":18,"is_retracted":false,"has_abstract":false,"ca_institutions":"Thompson Rivers University","funders":"","keywords":"Landscape connectivity; Computer science; Functional connectivity; Graph; Environmental science; Ecology; Biology; Theoretical computer science; Neuroscience","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001427496,0.0003779471,0.000278465,0.001334907,0.0002499588,0.0005651364,0.0006980787,0.0008461609,0.001174447],"category_scores_gemma":[0.008150874,0.0001798762,0.0004914489,0.001144046,0.0004821201,0.001151319,0.0004259501,0.0004094453,0.00007083374],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001359275,"about_ca_system_score_gemma":0.0003062177,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02324987,"about_ca_topic_score_gemma":0.02713322,"domain_scores_codex":[0.9995309,0.0002615814,0.00002034776,0.00008800795,0.00004461932,0.0000545591],"domain_scores_gemma":[0.9925231,0.005961499,0.0006166798,0.000299544,0.0003537114,0.0002455227],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001682887,0.00007089978,0.02508251,0.00002176004,0.000071617,0.00004561849,0.00006435631,0.9704245,0.0004214539,0.0007024135,0.0002511957,0.002675255],"study_design_scores_gemma":[0.00002021428,0.00009432596,0.01969649,0.000006770057,0.00002685189,0.00003127018,0.00008722111,0.9784694,0.0002697444,0.001140473,0.000143326,0.00001398947],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9972429,0.0000203574,0.002022853,0.0000459456,0.000003226438,0.00001119441,0.0002616198,0.00003553701,0.0003562353],"genre_scores_gemma":[0.9988343,0.000008423624,0.0008985504,0.000003804161,8.513882e-7,0.000008187327,0.0001756511,0.000005688534,0.00006448164],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02324987,"threshold_uncertainty_score":0.04622906,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03348422770367034,"score_gpt":0.2693229126922598,"score_spread":0.2358386849885895,"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."}}