{"id":"W6901846267","doi":"10.60692/q4ge6-2jq60","title":"IMPROVING DATA QUALITY AND MANAGEMENT FOR REMOTE SENSING ANALYSIS: USE-CASES AND EMERGING RESEARCH QUESTIONS","year":2023,"lang":"en","type":"article","venue":"Greater South Information System","topic":"Remote-Sensing Image Classification","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Data quality; Data management; Geospatial analysis; Data modeling; Data integration; Big data; Data virtualization; Quality (philosophy)","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001929701,0.0001244706,0.00019104,0.0009136969,0.0002826303,0.0005485653,0.0001032142,0.00006230419,2.974721e-7],"category_scores_gemma":[0.0002996599,0.0001247006,0.00002776955,0.000899689,0.00003608728,0.001069329,0.0001624406,0.0000900989,0.00002795538],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009286356,"about_ca_system_score_gemma":0.000007402134,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007219819,"about_ca_topic_score_gemma":0.000004750731,"domain_scores_codex":[0.9986433,0.00009543721,0.0005169418,0.0002207459,0.0002580724,0.0002654812],"domain_scores_gemma":[0.9988126,0.0001323477,0.0001015507,0.0006959903,0.0001894712,0.0000680895],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002349223,0.000004734706,0.06016773,0.03563884,0.004187133,0.00007844876,0.1292748,0.04265093,0.000984448,0.0016659,0.00388794,0.7212242],"study_design_scores_gemma":[0.0002045917,0.000004853164,0.07211801,0.0001361527,0.0001233587,0.00001253664,0.006881683,0.9200224,0.00005559162,0.000002032211,0.0003085413,0.0001302103],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4477581,0.000008724854,0.5503431,0.00008549517,0.0001513222,0.0005850142,0.000155981,0.0007472184,0.0001650711],"genre_scores_gemma":[0.9841673,0.000004705039,0.0155004,0.000009361384,0.00003764873,0.000003200446,0.0001982356,0.00001692913,0.00006225988],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8773715,"threshold_uncertainty_score":0.5289828,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2647868819306809,"score_gpt":0.3542100414340522,"score_spread":0.08942315950337126,"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."}}