{"id":"W7020779136","doi":"","title":"Managing public data for whose benefit?: a case study analysis of accessing land titles in the Canadian prairies","year":2020,"lang":"en","type":"dissertation","venue":"Mspace (University of Manitoba)","topic":"Land Rights and Reforms","field":"Agricultural and Biological Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Land registration; Context (archaeology); Public sector; Private sector; Land management; Jurisdiction; General partnership; Marketization; Public land; Service provider","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":[0.0001909753,0.00009078134,0.0002597157,0.00009940161,0.0004066361,0.00007033825,0.0006054295,0.00008638852,0.000007354046],"category_scores_gemma":[0.00001016769,0.00002525276,0.00007934296,0.0006134794,0.00003377781,0.000178768,0.00006035088,0.00008975602,5.366076e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002705079,"about_ca_system_score_gemma":0.00003840154,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.7357837,"about_ca_topic_score_gemma":0.999955,"domain_scores_codex":[0.9993936,0.0000319357,0.00008178212,0.0002142857,0.0001476718,0.0001307328],"domain_scores_gemma":[0.9995599,0.00005995035,0.0001514965,0.000110987,0.00006717613,0.00005044762],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001324056,0.0003721935,0.9116243,0.000264499,0.001691651,0.001159414,0.01163939,0.00003640065,0.0000622443,0.0002947522,0.001591707,0.07113107],"study_design_scores_gemma":[0.0001543182,0.00009868594,0.7361125,0.0000286867,0.0006315577,0.000003321376,0.246598,0.0008749496,0.000001191556,0.00005325254,0.01531722,0.0001262721],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9941063,0.00005109163,0.000001181288,0.004674766,0.00004276607,0.0002887454,0.0003308647,0.0000057987,0.000498512],"genre_scores_gemma":[0.997551,0.00003849335,0.00002569102,0.00001418885,0.00003110056,3.630939e-7,0.00199546,7.643166e-7,0.0003429299],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2641713,"threshold_uncertainty_score":0.3127557,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05539420559962556,"score_gpt":0.2461651562939312,"score_spread":0.1907709506943057,"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."}}