{"id":"W6906543930","doi":"10.17632/2p3x7cvsp9.1","title":"Online-Appendix for: An agent-based modelling approach to explore land-use planning and policy adoption at Curve Lake First Nation, Canada","year":2024,"lang":"en","type":"dataset","venue":"Data Archiving and Networked Services (DANS)","topic":"demographic modeling and climate adaptation","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Voting; Executable; Multinomial logistic regression; Point (geometry); R package; Field (mathematics); Descriptive statistics; Statistical analysis","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.001815029,0.0005189055,0.0005650288,0.0006857009,0.000855563,0.001132116,0.001729879,0.0001935149,0.000005231157],"category_scores_gemma":[0.0001224923,0.0004316937,0.00006597873,0.0007471947,0.0000595787,0.0006415962,0.0008879948,0.000388657,0.00001405042],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006813103,"about_ca_system_score_gemma":0.0002618413,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.1892772,"about_ca_topic_score_gemma":0.899161,"domain_scores_codex":[0.9954754,0.0002407434,0.000875443,0.001724559,0.001104335,0.00057959],"domain_scores_gemma":[0.9961803,0.001249592,0.0003818067,0.001622457,0.0001449339,0.0004209058],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000126358,0.00006137226,0.001417134,0.0004648465,0.00005332719,0.000006260975,0.001234378,0.5285517,5.998257e-7,0.000009094082,0.4666792,0.001395653],"study_design_scores_gemma":[0.0001785471,0.00003884284,0.0002925172,0.0004152013,0.00008493294,0.000007320478,0.0008971553,0.6032254,8.027181e-8,0.0002163424,0.3943446,0.000299143],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.04553116,0.0004543756,0.03945794,0.0002082351,0.0004000851,0.0004835237,0.9133704,0.0000741592,0.00002006726],"genre_scores_gemma":[0.01359429,0.0005026119,0.00453996,0.0006304911,0.0006349417,0.00005792661,0.9799391,0.00005289488,0.00004775575],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.7098838,"threshold_uncertainty_score":0.9999048,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2704767917933859,"score_gpt":0.3657096087900293,"score_spread":0.09523281699664349,"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."}}