{"id":"W2214546850","doi":"10.5623/cig2015-310","title":"GEOMATICS AND THE LAW Socio-Economic Value of the Indian Lands Registry","year":2015,"lang":"en","type":"article","venue":"GEOMATICA","topic":"Automated Road and Building Extraction","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Simon Fraser University; Natural Resources Canada","funders":"Natural Resources Canada; Aboriginal Affairs and Northern Development Canada","keywords":"Geomatics; Value (mathematics); Geography; Agricultural economics; Socioeconomics; Regional science; Sociology; Remote sensing; Economics; Statistics; Mathematics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005111721,0.0001392985,0.000408821,0.005504057,0.003057478,0.0101813,0.001185261,0.0008398284,0.006777094],"category_scores_gemma":[0.02807111,0.0003328968,0.0003337649,0.00684219,0.01120909,0.004968403,0.003274697,0.002045664,0.0004859262],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007267022,"about_ca_system_score_gemma":0.0039572,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03356065,"about_ca_topic_score_gemma":0.03531814,"domain_scores_codex":[0.9941743,0.00220858,0.0003609155,0.0005051588,0.002186775,0.0005643615],"domain_scores_gemma":[0.9781519,0.01234413,0.002625411,0.002704134,0.003153599,0.001020875],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.00003634469,0.00002871961,0.02475275,0.00002228863,0.00002072032,0.0001418115,0.000759306,0.001871472,0.0001007904,0.9589444,0.002073183,0.01124819],"study_design_scores_gemma":[0.00002853842,0.00005884242,0.1060149,0.0001827948,0.0001341604,0.00052175,0.008169618,0.01941232,0.0006597676,0.8048562,0.05987916,0.00008206129],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.3703149,0.001264555,0.01534923,0.02176618,0.0001652718,0.00008586461,0.001961849,0.0001198531,0.5889723],"genre_scores_gemma":[0.9954329,0.0001724324,0.0005318803,0.0001882195,0.0000595172,0.00001961196,0.0001093336,0.00001259516,0.003473396],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03356065,"threshold_uncertainty_score":0.06673056,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006427587235509835,"score_gpt":0.1968473152140489,"score_spread":0.190419727978539,"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."}}