{"id":"W4402262707","doi":"10.62973/12-159","title":"OWS-9 CCI Conflation with Provenance Engineering Report","year":2013,"lang":"en","type":"report","venue":"","topic":"Scientific Computing and Data Management","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Defence Science and Technology Group; Natural Resources Canada; U.S. Army Corps of Engineers; Defence Science and Technology Laboratory; National Geospatial-Intelligence Agency; Federal Aviation Administration; U.S. Geological Survey; National Aeronautics and Space Administration","keywords":"Conflation; Provenance; Computer science; Geology; Epistemology; Paleontology; Philosophy","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.02651739,0.001084664,0.0007507027,0.005403586,0.002774519,0.01025713,0.002219656,0.001961947,0.02084144],"category_scores_gemma":[0.04219954,0.0009838246,0.001389575,0.003649708,0.001837631,0.006675097,0.006017282,0.00393995,0.01450265],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006347788,"about_ca_system_score_gemma":0.02022951,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03988161,"about_ca_topic_score_gemma":0.02141814,"domain_scores_codex":[0.9707868,0.004614025,0.001796716,0.001654389,0.0196656,0.001482614],"domain_scores_gemma":[0.9520915,0.005876062,0.001398307,0.01538499,0.02391078,0.001338335],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0005238491,0.0004426388,0.005665156,0.0005400448,0.00006849703,0.0007684201,0.001906886,0.008728844,0.01122915,0.2500759,0.4316159,0.2884347],"study_design_scores_gemma":[0.00006990734,0.00009086855,0.001498612,0.00030875,0.00003070459,0.0003284109,0.0002572316,0.01730725,0.03094691,0.03115658,0.9179103,0.0000944906],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.01496565,0.0007147794,0.5729685,0.01153515,0.002503798,0.005335728,0.0301272,0.03402952,0.3278196],"genre_scores_gemma":[0.084199,0.001617872,0.6091262,0.002097786,0.0009758741,0.002962949,0.1015372,0.01290339,0.1845797],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.03988161,"threshold_uncertainty_score":0.1402391,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1847125609089232,"score_gpt":0.3931584469921435,"score_spread":0.2084458860832203,"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."}}