{"id":"W1981314985","doi":"10.1016/j.im.2010.04.001","title":"Governing the data commons: Policy, practice, and the advancement of science","year":2010,"lang":"en","type":"article","venue":"Information & Management","topic":"Data Quality and Management","field":"Decision Sciences","cited_by":31,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Canadian Space Agency; NASA Headquarters; Australian Government; Agência Espacial Brasileira; University of California Berkeley; National Aeronautics and Space Administration","keywords":"Data sharing; Commons; Intellectual property; Shared resource; Common-pool resource; Natural resource; Global commons; Political science; Knowledge management; Data science; Business; Computer science; Law; Economics; Computer security; Ecology","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"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":[0.02140414,0.00008896119,0.0001252909,0.0002505007,0.0005854513,0.0008873424,0.003387013,0.00001450008,0.00005693461],"category_scores_gemma":[0.005547191,0.00004390222,0.00002308243,0.00106589,0.001486137,0.006395699,0.004368827,0.0001358553,0.0001862638],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002284598,"about_ca_system_score_gemma":0.0000560923,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000274331,"about_ca_topic_score_gemma":0.0001051765,"domain_scores_codex":[0.9965949,0.0001303776,0.0007425785,0.0002002166,0.002138509,0.0001934417],"domain_scores_gemma":[0.9955552,0.00104725,0.0007283769,0.002370997,0.000251461,0.00004676959],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00003113966,0.0000144896,0.00001161352,0.00001028536,0.00001555993,1.604656e-7,0.001216728,0.00008035578,0.000002042316,0.6473666,0.008298015,0.342953],"study_design_scores_gemma":[0.0005798814,0.000009930513,0.00288329,0.000006959023,0.00002488899,0.000002279285,0.01365811,0.005456223,0.00001012124,0.008337206,0.9689741,0.00005700945],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.004950289,0.0001284527,0.218052,0.2393125,0.001725183,0.003046012,0.0003176444,0.00007309528,0.5323948],"genre_scores_gemma":[0.9675776,0.0007443005,0.01344069,0.01593252,0.0001051192,0.0000898644,0.00009124499,0.000006331207,0.002012287],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9626274,"threshold_uncertainty_score":0.8556663,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08970413318049758,"score_gpt":0.4307513392214479,"score_spread":0.3410472060409503,"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."}}