{"id":"W2157607668","doi":"10.5539/jms.v1n1p124","title":"Economic Analysis on the Tragedy of the Commons of River","year":2011,"lang":"en","type":"article","venue":"Journal of Management and Sustainability","topic":"Water resources management and optimization","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Tragedy of the commons; Commons; Transaction cost; Property rights; Common-pool resource; Government (linguistics); Institution; Institutional economics; Database transaction; Exploit; Tragedy (event); Compensation (psychology); Mechanism (biology); Economics; Natural resource economics; Law and economics; Microeconomics; Neoclassical economics; Political science; Sociology; Law; Social science; Computer science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005504715,0.00006664809,0.0001642195,0.0001439246,0.00003672161,0.00000932185,0.0002187768,0.00001841605,0.0000479977],"category_scores_gemma":[0.00001136968,0.00003679565,0.000150897,0.0001769534,0.00009172941,0.00006877322,0.00006122411,0.00008165304,1.872587e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005212381,"about_ca_system_score_gemma":0.000004293099,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002240169,"about_ca_topic_score_gemma":0.00001694022,"domain_scores_codex":[0.9994099,0.00006362663,0.0002961728,0.00004997631,0.0001024404,0.00007785531],"domain_scores_gemma":[0.999536,0.00003419756,0.0001511007,0.0002138383,0.00004841555,0.00001645481],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001470295,0.0001751542,0.49634,0.0005865096,0.002606203,0.000005852336,0.005867792,0.4719687,0.000001635277,0.0159398,0.001129369,0.00523203],"study_design_scores_gemma":[0.0003774232,0.0000931981,0.9691239,0.0000176613,0.0009700062,3.660975e-7,0.003021034,0.01925201,0.0002623661,0.00540543,0.001392007,0.00008459496],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.989639,0.00005082582,0.002264431,0.0001730386,0.00004961932,0.0001806202,0.00000115714,0.000004603285,0.007636682],"genre_scores_gemma":[0.9996557,0.00005076242,0.00009948661,0.00000882149,0.000008709312,0.000001326724,2.277197e-7,0.000003973108,0.0001710127],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4727839,"threshold_uncertainty_score":0.1500483,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008342354984795427,"score_gpt":0.1796580420886179,"score_spread":0.1713156871038224,"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."}}