{"id":"W2130905133","doi":"10.1890/06-0239","title":"PREDICTING INVASION RISK USING MEASURES OF INTRODUCTION EFFORT AND ENVIRONMENTAL NICHE MODELS","year":2007,"lang":"en","type":"article","venue":"Ecological Applications","topic":"Marine Ecology and Invasive Species","field":"Environmental Science","cited_by":152,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta; University of Windsor","funders":"University of Alberta","keywords":"Biological dispersal; Eriocheir; Range (aeronautics); Habitat; Fishery; Ecology; Geography; Chinese mitten crab; Environmental niche modelling; Niche; Ecological niche; Environmental science; Biology; Population","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002317988,0.0006986111,0.0003701097,0.001381844,0.0001788609,0.0006620339,0.000321351,0.0005542747,0.0004057733],"category_scores_gemma":[0.008355443,0.0002084325,0.0005071055,0.0005309676,0.0003192142,0.0007200856,0.0005470854,0.0004064504,0.00009107921],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005363393,"about_ca_system_score_gemma":0.0003557498,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004922333,"about_ca_topic_score_gemma":0.005197937,"domain_scores_codex":[0.9993499,0.0002843463,0.00006142915,0.0001368512,0.0001030663,0.00006438426],"domain_scores_gemma":[0.9926708,0.005061049,0.001250385,0.0003097875,0.0004311134,0.0002770012],"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":[0.0002094213,0.0001775536,0.3715255,0.00001834579,0.0002331605,0.00009598728,0.00005952113,0.6087236,0.0006674438,0.0002764754,0.0001367627,0.01787626],"study_design_scores_gemma":[0.000008227387,0.0001374842,0.03564671,0.000005348106,0.00002512486,0.00004528348,0.00002774816,0.9632282,0.0003313131,0.0004814051,0.00005228267,0.00001083872],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.987307,0.0000567496,0.01195212,0.00004799242,0.000003637671,0.00001446825,0.0001361822,0.0000824891,0.0003993903],"genre_scores_gemma":[0.9950044,0.00002805323,0.004585462,0.000008348525,0.000003556019,0.00001370702,0.0002183248,0.000005262106,0.0001329448],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004922333,"threshold_uncertainty_score":0.01225889,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02475145242360457,"score_gpt":0.224002966358894,"score_spread":0.1992515139352894,"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."}}