{"id":"W3095028410","doi":"","title":"Green team paper: Falling off the cliff: When systems go nonlinear","year":2005,"lang":"en","type":"article","venue":"","topic":"Simulation Techniques and Applications","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"","keywords":"Falling (accident); Cliff; History; Archaeology; Psychology","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":[0.003531727,0.0007092394,0.0007467527,0.000556188,0.001483768,0.003091415,0.001247252,0.003411874,0.007577012],"category_scores_gemma":[0.01966831,0.0002711332,0.0007018399,0.0007186261,0.003399487,0.004377814,0.001640121,0.002766283,0.001501016],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001765462,"about_ca_system_score_gemma":0.001884426,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004312046,"about_ca_topic_score_gemma":0.003886242,"domain_scores_codex":[0.9984009,0.0007037735,0.00007332499,0.0002956982,0.0004317303,0.00009464574],"domain_scores_gemma":[0.990527,0.006295397,0.0006670456,0.0005926504,0.001385252,0.000532746],"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":[0.0004045074,0.00007593858,0.006790674,0.0005281165,0.0001473053,0.0007107893,0.001165983,0.1322912,0.001764331,0.5691803,0.1731268,0.113814],"study_design_scores_gemma":[0.00007060241,0.0001537995,0.001686671,0.0003179459,0.00006975498,0.0003300148,0.0006729382,0.2467408,0.003507655,0.6044396,0.1418849,0.0001254266],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04449944,0.008837732,0.7520406,0.122379,0.008015815,0.0001726821,0.0005375998,0.001015782,0.06250139],"genre_scores_gemma":[0.7709976,0.008359029,0.1141775,0.01649374,0.003301965,0.0002439805,0.0003901128,0.0007456515,0.08529045],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007577012,"threshold_uncertainty_score":0.02534759,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09552600298276405,"score_gpt":0.3869211152051126,"score_spread":0.2913951122223486,"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."}}