{"id":"W4280541891","doi":"10.3389/fevo.2022.830822","title":"Missing Interactions: The Current State of Multispecies Connectivity Analysis","year":2022,"lang":"en","type":"article","venue":"Frontiers in Ecology and Evolution","topic":"Wildlife-Road Interactions and Conservation","field":"Environmental Science","cited_by":51,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Carleton University; Environment and Climate Change Canada; Centre For Cold Ocean Resources Engineering","funders":"Environment and Climate Change Canada","keywords":"Metapopulation; Landscape connectivity; Seascape; Metric (unit); Computer science; Field (mathematics); Ecology; Data science; Environmental resource management; Habitat; Biology; Environmental science; Biological dispersal; Population; Engineering","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0002794136,0.00004675815,0.00009966441,0.0001168214,0.0003073109,0.000006093757,0.00006446026,0.000008717616,0.0001693242],"category_scores_gemma":[0.00004569762,0.00004128452,0.00003726257,0.0004406773,0.0001401897,0.0001647798,0.00009252132,0.0001782401,0.000002177332],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003398343,"about_ca_system_score_gemma":0.00001024322,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003768845,"about_ca_topic_score_gemma":0.001963398,"domain_scores_codex":[0.9993592,0.0001876564,0.00015357,0.00013356,0.00007226232,0.00009374426],"domain_scores_gemma":[0.9997144,0.00007201557,0.000105387,0.00008872669,0.000006282597,0.00001316701],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00003240223,0.00007243917,0.928112,0.000001324846,0.00003423293,2.791716e-7,0.0003305917,0.01715698,0.00008705723,0.00002337275,0.002887113,0.05126214],"study_design_scores_gemma":[0.00009597551,0.00002593551,0.9132541,0.000001359542,0.00004095457,0.000002150717,0.000367862,0.07852446,0.00001017399,0.001805032,0.005832258,0.00003974593],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9879748,0.0002031121,0.01006284,0.000656468,0.0007638055,0.0001005164,0.000008482179,0.00000623655,0.0002237828],"genre_scores_gemma":[0.9992963,0.00003863869,0.000429701,0.00004733304,0.000006912859,0.00004066388,0.000006453142,0.000001807212,0.0001321751],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06136748,"threshold_uncertainty_score":0.2363618,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007934135960346053,"score_gpt":0.2333811927905992,"score_spread":0.2254470568302531,"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."}}