{"id":"W1981366504","doi":"10.1111/ddi.12215","title":"Spatial distribution of marine invasive species: environmental, demographic and vector drivers","year":2014,"lang":"en","type":"article","venue":"Diversity and Distributions","topic":"Marine Ecology and Invasive Species","field":"Environmental Science","cited_by":77,"is_retracted":false,"has_abstract":true,"ca_institutions":"Fisheries and Oceans Canada; Royal British Columbia Museum; University of British Columbia","funders":"Environment Canada; Natural Sciences and Engineering Research Council of Canada; North Pacific Marine Science Organization","keywords":"Spatial analysis; Geography; Spatial distribution; Population; Ecology; Marine spatial planning; Distribution (mathematics); Biodiversity; Spatial ecology; Marine ecosystem; Species distribution; Fishery; Ecosystem; Habitat; Biology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.000094515,0.0001000201,0.0001290164,0.00001945073,0.0009144388,0.000008797478,0.00009676861,0.00006840515,0.002091918],"category_scores_gemma":[0.00009899306,0.0001026183,0.00004346204,0.00008958811,0.001052394,0.0001505611,0.001613128,0.00008356869,0.00002304887],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006016194,"about_ca_system_score_gemma":0.000003291355,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005975305,"about_ca_topic_score_gemma":0.0006048213,"domain_scores_codex":[0.999364,0.00004526508,0.0001044071,0.0002120589,0.0001184425,0.000155805],"domain_scores_gemma":[0.999619,0.0000969372,0.0000662924,0.0001117952,0.00000569392,0.0001002966],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0000140251,0.00006744592,0.9924576,0.000006798822,0.00001479509,0.00000128537,0.0001206312,0.000004507733,0.0005545524,0.005234861,0.0009547767,0.0005687479],"study_design_scores_gemma":[0.0003423101,0.0001062344,0.9920086,0.000002868175,0.00004420884,0.00000357029,0.000173182,0.00008216767,0.000521806,0.001260511,0.005348634,0.0001058922],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9942926,0.000007154491,0.002331547,0.000212017,0.0000531182,0.00009804578,0.0004623555,0.00001338636,0.002529799],"genre_scores_gemma":[0.9990603,0.0002193536,0.00004270893,0.00004014326,0.00001641593,0.000001908845,0.0004565986,0.000001805445,0.0001607546],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004767735,"threshold_uncertainty_score":0.9988203,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007588483944054718,"score_gpt":0.1660712889747614,"score_spread":0.1584828050307067,"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."}}