{"id":"W2145227879","doi":"10.1890/09-1452.1","title":"Is invasion history a useful tool for predicting the impacts of the world's worst aquatic invasive species?","year":2011,"lang":"en","type":"article","venue":"Ecological Applications","topic":"Aquatic Invertebrate Ecology and Behavior","field":"Environmental Science","cited_by":162,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Invasive species; Context (archaeology); Introduced species; Ecology; Biomass (ecology); Biology; Estimation","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":[0.01783243,0.001654797,0.002104674,0.009274026,0.0003855197,0.00243136,0.001623718,0.001234948,0.001805217],"category_scores_gemma":[0.03799646,0.0007664538,0.008794338,0.005508433,0.0007562044,0.002750712,0.001084219,0.0018304,0.0003036043],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008495572,"about_ca_system_score_gemma":0.001103563,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009850893,"about_ca_topic_score_gemma":0.01652685,"domain_scores_codex":[0.9955599,0.002514681,0.0005331161,0.0008888454,0.0004105261,0.00009293338],"domain_scores_gemma":[0.9426149,0.04628037,0.006154542,0.002901024,0.001398211,0.0006509409],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004382529,0.0001088955,0.760119,0.007710213,0.07653801,0.000450187,0.0006012762,0.06368675,0.001553247,0.001699552,0.002641639,0.08445299],"study_design_scores_gemma":[0.0001902638,0.001747849,0.5861189,0.006070354,0.09366632,0.001022623,0.001721106,0.2531356,0.002220567,0.02859031,0.02503626,0.0004799834],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5200597,0.3291433,0.1160929,0.01437461,0.0007576958,0.0002839117,0.01133666,0.001386112,0.006565173],"genre_scores_gemma":[0.9538359,0.01785897,0.02515099,0.0007375723,0.0003043438,0.00008263842,0.001633418,0.00009880983,0.0002973725],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01783243,"threshold_uncertainty_score":0.09430802,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05650320433434411,"score_gpt":0.2394417670952898,"score_spread":0.1829385627609457,"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."}}