{"id":"W2022963522","doi":"10.1002/ieam.109","title":"Traits-based approaches in bioassessment and ecological risk assessment: Strengths, weaknesses, opportunities and threats","year":2010,"lang":"en","type":"article","venue":"Integrated Environmental Assessment and Management","topic":"Species Distribution and Climate Change","field":"Environmental Science","cited_by":114,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Strengths and weaknesses; Trait; Stressor; Biodiversity; Ecology; Environmental resource management; Transferability; Data science; Risk analysis (engineering); Environmental planning; Biology; Geography; Computer science; Psychology; Business; Environmental science; Machine learning","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.03000032,0.002129897,0.00164822,0.009795636,0.001240434,0.007284232,0.003070974,0.002108185,0.001506967],"category_scores_gemma":[0.03545475,0.0009705094,0.001904604,0.007058707,0.004636392,0.005609084,0.006016155,0.003554008,0.0008070566],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002588629,"about_ca_system_score_gemma":0.002232415,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008673875,"about_ca_topic_score_gemma":0.01154403,"domain_scores_codex":[0.9763914,0.01285456,0.001510788,0.002148035,0.006642465,0.0004527321],"domain_scores_gemma":[0.9571373,0.02335786,0.006671344,0.00459017,0.007425,0.0008183545],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001780185,0.000215874,0.1258389,0.001994113,0.0009382603,0.0004504923,0.002811059,0.02539716,0.008718863,0.08501956,0.003310686,0.745127],"study_design_scores_gemma":[0.00006539196,0.0008941854,0.1743439,0.002236595,0.0006496652,0.003155368,0.006329858,0.2195644,0.01662279,0.4790356,0.09625546,0.0008468368],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"review","genre_scores_codex":[0.03177029,0.007270083,0.9415275,0.006527263,0.0003419043,0.0003080611,0.000527687,0.0005561468,0.01117113],"genre_scores_gemma":[0.2905724,0.005765238,0.6980231,0.001743702,0.0003202737,0.000439983,0.0003262335,0.000156411,0.002652633],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.03000032,"threshold_uncertainty_score":0.1586588,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04386124306454255,"score_gpt":0.2739231717131472,"score_spread":0.2300619286486046,"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."}}