{"id":"W2337258059","doi":"10.1079/9781780643946.0206","title":"Making invasion models useful for decision makers: incorporating uncertainty, knowledge gaps and decision-making preferences.","year":2015,"lang":"en","type":"book-chapter","venue":"CABI eBooks","topic":"Forest Management and Policy","field":"Environmental Science","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Natural Resources Canada; Canadian Forest Service","funders":"","keywords":"PEST analysis; Portfolio; Valuation (finance); Identification (biology); Actuarial science; Asset (computer security); Environmental resource management; Computer science; Econometrics; Ecology; Risk analysis (engineering); Business; Economics; Biology; Marketing; Finance","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":[0.002972583,0.0009978286,0.000612947,0.0006176438,0.000536876,0.003561922,0.001039713,0.001213434,0.006384154],"category_scores_gemma":[0.00693428,0.0004763539,0.0006489315,0.0009910488,0.001031112,0.003804196,0.001297969,0.001798253,0.0008250968],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001572735,"about_ca_system_score_gemma":0.001308045,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003314369,"about_ca_topic_score_gemma":0.009367339,"domain_scores_codex":[0.9993636,0.0004086783,0.00001832484,0.00005865236,0.0001175099,0.00003329333],"domain_scores_gemma":[0.9957889,0.003759847,0.0001305085,0.0000914066,0.0001317081,0.00009768879],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003977185,0.00007899023,0.001649659,0.0004363031,0.000112042,0.0002067841,0.001308178,0.2786939,0.0006454651,0.5753007,0.0235939,0.1179345],"study_design_scores_gemma":[0.000008269492,0.00002609747,0.0003881156,0.0002728068,0.00003132521,0.00006213126,0.0004568323,0.2433266,0.000227721,0.7177721,0.0374014,0.00002659667],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03113692,0.01039374,0.7946333,0.01274203,0.0006095084,0.0001538579,0.0008188604,0.0003818556,0.1491299],"genre_scores_gemma":[0.4736086,0.01499606,0.4719286,0.001313299,0.000437688,0.0004089147,0.0009412579,0.0002646821,0.03610096],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006384154,"threshold_uncertainty_score":0.02135718,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1055811362923263,"score_gpt":0.311638013045839,"score_spread":0.2060568767535127,"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."}}