{"id":"W3096797053","doi":"10.15666/aeer/1302_569582","title":"DEVELOPING A QUANTITATIVE INDEX OF INTEGRITY AS A COMPREHENSIVE MEASURE IN ECOLOGICAL CHANGE ANALYSIS","year":2015,"lang":"en","type":"article","venue":"Applied Ecology and Environmental Research","topic":"Sustainability and Ecological Systems Analysis","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"University of Waterloo","keywords":"Index (typography); Measure (data warehouse); Change analysis; Ecology; Environmental resource management; Geography; Environmental science; Computer science; Physical geography; Data mining; Biology; World Wide Web","routes":{"ca_aff":true,"ca_fund":true,"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":[0.002988397,0.0005177457,0.0004903647,0.007101823,0.0007521681,0.002126993,0.0005435999,0.000517686,0.001355211],"category_scores_gemma":[0.007004904,0.0001571519,0.0005499832,0.005214924,0.001018793,0.002501327,0.001414028,0.0006874917,0.0001887386],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001020396,"about_ca_system_score_gemma":0.0007625706,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002793092,"about_ca_topic_score_gemma":0.005211041,"domain_scores_codex":[0.997769,0.0005883579,0.0003165627,0.0002145298,0.0009723805,0.0001392879],"domain_scores_gemma":[0.9952514,0.001314397,0.00120007,0.0004247938,0.001520075,0.0002893054],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001358982,0.0002841438,0.6725004,0.0005219833,0.0004197222,0.000309103,0.002779341,0.02236368,0.01021553,0.01914493,0.002727235,0.268598],"study_design_scores_gemma":[0.00001350647,0.0005771708,0.8484768,0.0002391275,0.0001624448,0.0005975902,0.006912712,0.1012548,0.007860515,0.0202861,0.01348443,0.0001347488],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.6627163,0.0008643707,0.3103637,0.0005121657,0.00007966105,0.000519541,0.002097507,0.000363602,0.02248325],"genre_scores_gemma":[0.9146159,0.0001945376,0.08295371,0.00003237624,0.00003198751,0.000268447,0.001050487,0.00001937768,0.0008331972],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.007101823,"threshold_uncertainty_score":0.01580435,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1971177708820132,"score_gpt":0.3743645421004302,"score_spread":0.1772467712184171,"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."}}