{"id":"W1517515132","doi":"","title":"Land in Conflict: Managing and Resolving Land Use Disputes: Chapter 1","year":2013,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Environmental Conservation and Management","field":"Environmental Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Negotiation; Process (computing); Work (physics); Quality (philosophy); Action (physics); Space (punctuation); Conflict resolution; Public relations; Land use; Political science; Set (abstract data type); Public land; Law and economics; Business; Law; Engineering; Economics; Computer science; Civil engineering","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":[],"consensus_categories":[],"category_scores_codex":[0.0003563698,0.00009675296,0.00008237105,0.0000472393,0.0001005748,0.00009645002,0.0001038112,0.00002588084,0.0006214316],"category_scores_gemma":[0.0000111055,0.00008383195,0.00002020012,0.00005570047,0.00006300483,0.000536102,0.0001298119,0.0004114457,0.0001631342],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003010035,"about_ca_system_score_gemma":0.000008476454,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002213011,"about_ca_topic_score_gemma":0.006994753,"domain_scores_codex":[0.9987339,0.00002771776,0.0001574242,0.0001652562,0.0001535388,0.0007621506],"domain_scores_gemma":[0.9997569,0.00002358967,0.00005573149,0.00009429121,0.000001785203,0.00006764439],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000009040952,0.00002421005,0.9733339,0.000002620537,0.0000134324,0.000005474874,0.0002163999,0.0001281936,0.0004357829,0.004557704,0.0001912253,0.02108203],"study_design_scores_gemma":[0.001071348,0.0001153659,0.9420787,0.00002723637,0.00001453151,0.0001002082,0.0008487096,0.002637016,0.00002106362,0.02274493,0.03007009,0.0002707843],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9929464,0.0003047404,0.001074513,0.002535084,0.00003081084,0.0001722524,3.353171e-7,0.00001259491,0.002923195],"genre_scores_gemma":[0.9922662,0.003209248,0.0001982341,0.001149358,0.00001719111,0.000007314847,0.000001232728,0.0000112557,0.003139914],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03125516,"threshold_uncertainty_score":0.680424,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00990745371984991,"score_gpt":0.1998240542547549,"score_spread":0.189916600534905,"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."}}