{"id":"W4283032704","doi":"10.31390/gradschool_theses.5270","title":"Mapping Louisiana's Missing: Spatiotemporal Profiling of Louisiana's Missing Persons- An Experimental Application of Geographic Information Systems and Forensic Anthropology","year":2021,"lang":"en","type":"dissertation","venue":"","topic":"Data-Driven Disease Surveillance","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Forensic anthropology; Missing data; Profiling (computer programming); Data science; Population; Geography; Criminology; Genealogy; Sociology; History; Computer science; Demography; Archaeology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001525287,0.0002632504,0.0002369312,0.002154599,0.001913885,0.001195647,0.000821717,0.0004773294,0.00203336],"category_scores_gemma":[0.004873218,0.0002049178,0.0003455053,0.00347267,0.0007105414,0.0008752838,0.001702162,0.0006303681,0.0003700053],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002462724,"about_ca_system_score_gemma":0.002258971,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1300641,"about_ca_topic_score_gemma":0.2813011,"domain_scores_codex":[0.9987767,0.0005578692,0.00006551835,0.0002789893,0.0002045582,0.0001163074],"domain_scores_gemma":[0.9965783,0.0009235912,0.0006107393,0.0005224799,0.001209156,0.000155683],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004770209,0.0009592535,0.8180574,0.0002502549,0.0001652006,0.001008981,0.03354852,0.006347221,0.01145545,0.004866869,0.006960417,0.1159034],"study_design_scores_gemma":[0.00004043613,0.001007259,0.8590813,0.0001642899,0.0001548365,0.0004846641,0.07637872,0.02619761,0.00706768,0.002231959,0.02707579,0.0001154898],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9910173,0.00006757531,0.003064606,0.0001784221,0.000006746838,0.0001857291,0.00221887,0.00005860567,0.003202126],"genre_scores_gemma":[0.9814889,0.0001273605,0.01284132,0.00006825573,0.000006076127,0.0003991628,0.002887195,0.0000243267,0.00215746],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1300641,"threshold_uncertainty_score":0.2586141,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0142010731034416,"score_gpt":0.3001517904189895,"score_spread":0.2859507173155479,"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."}}