{"id":"W2905050592","doi":"10.1007/978-3-319-95101-0_8","title":"Sampling Wild Species to Conserve Genetic Diversity","year":2018,"lang":"en","type":"book-chapter","venue":"","topic":"Genetic and Environmental Crop Studies","field":"Agricultural and Biological Sciences","cited_by":13,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Agriculture and Agri-Food Canada; University of British Columbia","keywords":"Outcrossing; Sampling (signal processing); Genetic diversity; Selection (genetic algorithm); Population; Environmental niche modelling; Sample (material); Biology; Sample size determination; Geography; Ecology; Statistics; Computer science; Ecological niche; Habitat; Mathematics; Machine learning","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00003565697,0.0002129976,0.0002088709,0.000006757026,0.0004300296,0.00002669518,0.0002314351,0.0001217584,0.01969409],"category_scores_gemma":[0.000004161571,0.00007785764,0.0001067374,0.00001590229,0.0001720633,0.00001174583,0.001142848,0.00007045342,0.001881075],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003263583,"about_ca_system_score_gemma":0.00000141118,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001475167,"about_ca_topic_score_gemma":0.001179185,"domain_scores_codex":[0.9991269,0.000004689331,0.0001320021,0.0003403183,0.0001992098,0.0001968895],"domain_scores_gemma":[0.9997257,0.000042923,0.00004642922,0.00005783097,0.00001988794,0.000107228],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002767195,0.0002270547,0.1438649,0.0001020793,0.001014898,0.00009858772,0.002411346,0.00003319062,0.04616984,0.01532845,0.6178249,0.172648],"study_design_scores_gemma":[0.00003256057,0.0002701675,0.2674218,0.00002473026,0.00003346935,0.000002853923,0.0001637214,2.283434e-7,0.00008955294,0.003454169,0.7281862,0.0003204914],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.2706611,0.0002521131,0.00001198263,0.0007892298,0.0001748057,0.000237263,0.0001035212,0.00005106347,0.7277189],"genre_scores_gemma":[0.09165404,0.000364566,0.0007534356,0.001037747,0.0005041409,0.000002310636,0.00002680405,0.000001570967,0.9056554],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.179007,"threshold_uncertainty_score":0.9988961,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06395757802083384,"score_gpt":0.1963748119878791,"score_spread":0.1324172339670453,"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."}}