{"id":"W2115662142","doi":"10.1016/j.ecolmodel.2006.04.015","title":"Managing sparse data in biological invasions: a simulation study","year":2006,"lang":"en","type":"article","venue":"Ecological Modelling","topic":"Plant and animal studies","field":"Agricultural and Biological Sciences","cited_by":15,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"","keywords":"Computer science; Ecology; Data science; Environmental science; Biology","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":[0.008947015,0.0009249436,0.001338302,0.001485855,0.001073606,0.001953992,0.002618607,0.003269913,0.003395412],"category_scores_gemma":[0.04673989,0.0008969141,0.001280446,0.002088709,0.002151142,0.004731995,0.001813013,0.003017129,0.0001967457],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002575322,"about_ca_system_score_gemma":0.001410719,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03279097,"about_ca_topic_score_gemma":0.02661981,"domain_scores_codex":[0.9976314,0.001535262,0.00009666681,0.0002224782,0.0001694156,0.0003446352],"domain_scores_gemma":[0.8574098,0.132306,0.004307529,0.002464684,0.001843353,0.001668694],"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":[0.0002838229,0.0004211123,0.006687387,0.00005737092,0.0000637683,0.0001045258,0.0001626272,0.9831737,0.0001673012,0.004783263,0.0006122378,0.003483019],"study_design_scores_gemma":[0.00008033179,0.0001261978,0.0008229482,0.000007912487,0.00002933656,0.00003770059,0.0001073219,0.9957975,0.0000876376,0.002758746,0.0001329159,0.00001159197],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9757974,0.0004547916,0.01948265,0.001067049,0.00002976039,0.00008704657,0.0003508698,0.00007066989,0.002659753],"genre_scores_gemma":[0.9912665,0.0002407118,0.006873236,0.00007514938,0.00001607338,0.00006787427,0.0001849852,0.00002866042,0.001246845],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03279097,"threshold_uncertainty_score":0.06520021,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3782367534780159,"score_gpt":0.2785762857147799,"score_spread":0.099660467763236,"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."}}