{"id":"W31481955","doi":"10.29173/alr127","title":"Spatial Data Quality: The Duty to Warn Users of Risks Associated with Using Spatial Data","year":2011,"lang":"en","type":"article","venue":"Alberta Law Review","topic":"Medical Malpractice and Liability Issues","field":"Health Professions","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Harm; Context (archaeology); Misrepresentation; Quality (philosophy); Spatial analysis; Data quality; Liability; Duty to warn; Damages; Spatial contextual awareness; Business; Computer science; Law; Confidentiality; Computer security; Geography; Service (business); Political science; Marketing","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":true,"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":[0.02757888,0.0003653005,0.0006187435,0.002001155,0.005900546,0.009808641,0.003002408,0.01676642,0.0031273],"category_scores_gemma":[0.07944592,0.0007639548,0.000745836,0.002063186,0.03222043,0.008567654,0.006977015,0.008646053,0.0008881658],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.008014651,"about_ca_system_score_gemma":0.02481515,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1098171,"about_ca_topic_score_gemma":0.07086728,"domain_scores_codex":[0.9517041,0.0135393,0.003497332,0.003867434,0.02406985,0.003321832],"domain_scores_gemma":[0.9148775,0.05081865,0.00742692,0.01304211,0.0121885,0.001646302],"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":[0.00001784012,0.00003150907,0.004760178,0.0001155385,0.00002583842,0.0006703635,0.007715042,0.0009287391,0.0005080128,0.9346057,0.02027855,0.03034274],"study_design_scores_gemma":[0.00006586355,0.0001687288,0.01141536,0.0016422,0.00009459015,0.003219444,0.01018057,0.003264461,0.001764687,0.534923,0.4330563,0.0002048878],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.06508903,0.008241925,0.09884283,0.5292131,0.001173223,0.0002613913,0.000479731,0.0001945673,0.2965043],"genre_scores_gemma":[0.8484849,0.005408296,0.02518167,0.08103664,0.001391407,0.000195573,0.0001847896,0.00009048333,0.0380263],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.1098171,"threshold_uncertainty_score":0.2183558,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.6119162556620042,"score_gpt":0.5516200971264754,"score_spread":0.06029615853552883,"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."}}