{"id":"W7065403425","doi":"","title":"Enhancing connectivity through corridors for the dispersal and biodiversity conversation of forest herbaceous species in agroecosystems","year":2011,"lang":"en","type":"dissertation","venue":"eScholarship@McGill (McGill)","topic":"Magnetic confinement fusion research","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; McGill University","keywords":"Biological dispersal; Agroecosystem; Biodiversity; Seed dispersal; Range (aeronautics); Landscape connectivity; Herbaceous plant; Fragmentation (computing); Climate change","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003169611,0.0001393469,0.000131099,0.0005679879,0.0007923231,0.0005773404,0.0002385906,0.0001444645,0.003365584],"category_scores_gemma":[0.0007390048,0.00007312126,0.000136196,0.0004882872,0.000380531,0.0004524955,0.0005288944,0.0002374417,0.000153796],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001383862,"about_ca_system_score_gemma":0.0008149729,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.09030798,"about_ca_topic_score_gemma":0.4389702,"domain_scores_codex":[0.9998997,0.0000279306,0.000002834501,0.00001878883,0.000008429402,0.00004215581],"domain_scores_gemma":[0.9995067,0.00007655549,0.0001324047,0.00003811105,0.00006098934,0.0001852374],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002653736,0.0001542128,0.8813443,0.0001407516,0.00008954846,0.0004322231,0.002632665,0.001417373,0.02972544,0.001154367,0.001085271,0.08155844],"study_design_scores_gemma":[0.000005855196,0.00003948345,0.9971865,0.00001375963,0.00001108616,0.00005558446,0.000537698,0.0003781052,0.0002348116,0.0001257126,0.001406944,0.000004445075],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9970773,0.000100534,0.0004545375,0.00006196686,0.000001540582,0.00001825992,0.0000949785,0.000008297918,0.00218254],"genre_scores_gemma":[0.9975243,0.00009397809,0.001549928,0.00001743467,0.00000167779,0.00001421826,0.0001057487,0.000002933707,0.0006898425],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09030798,"threshold_uncertainty_score":0.1795647,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02007751828982359,"score_gpt":0.2349396599938913,"score_spread":0.2148621417040677,"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."}}