{"id":"W6948544189","doi":"10.5061/dryad.2rd20f3","title":"Data from: Habitat connectivity is determined by the scale of habitat loss and dispersal strategy","year":2018,"lang":"en","type":"dataset","venue":"Data Archiving and Networked Services (DANS)","topic":"Species Distribution and Climate Change","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Biological dispersal; Habitat; Range (aeronautics); Landscape connectivity; Scale (ratio)","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":[0.001408619,0.001801246,0.001284724,0.003181555,0.0008209539,0.002519017,0.002542527,0.001524802,0.07642904],"category_scores_gemma":[0.007865175,0.0007328441,0.0009300148,0.005744862,0.0005169944,0.001397502,0.002370828,0.001820322,0.06571468],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001466873,"about_ca_system_score_gemma":0.001887197,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02565151,"about_ca_topic_score_gemma":0.03720354,"domain_scores_codex":[0.9989457,0.0001380254,0.0001747502,0.0002916807,0.0002862699,0.0001636861],"domain_scores_gemma":[0.9974419,0.0007124619,0.0004764652,0.0005631098,0.0005538664,0.0002522747],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.00009779554,0.00002786599,0.005770958,0.001414532,0.00008366826,0.00006299449,0.0001106134,0.0007068838,0.0003598853,0.001209716,0.9859003,0.004254688],"study_design_scores_gemma":[0.0002968374,0.00001336662,0.01479894,0.0004070295,0.00004249371,0.00007586102,0.0001273855,0.0005385607,0.0004404641,0.001815215,0.9814087,0.00003525393],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0002298848,0.00003618695,0.00007839867,0.00005147825,0.00001180683,0.000006452094,0.99891,0.0001747021,0.0005012332],"genre_scores_gemma":[0.0009403029,0.00005609576,0.0003309213,0.00002797715,0.000004677431,0.00006133156,0.998063,0.00007240401,0.000443279],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.07642904,"threshold_uncertainty_score":0.2556806,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03248030282683541,"score_gpt":0.271726354890546,"score_spread":0.2392460520637106,"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."}}