{"id":"W3004117731","doi":"","title":"Eigenpattern analysis of eastern Canadian GPS data","year":2004,"lang":"en","type":"article","venue":"AGUSM","topic":"Geographic Information Systems Studies","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Global Positioning System; Geography; Remote sensing; Geodesy; Computer science; Telecommunications","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004941088,0.00005198623,0.0001553095,0.0004013198,0.000262768,0.00002866925,0.0004449738,0.00004349274,0.00009411106],"category_scores_gemma":[0.00006069655,0.00005048059,0.00005493632,0.001123599,0.0001186996,0.0002421707,0.00006221858,0.00003611892,0.0001029596],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000602343,"about_ca_system_score_gemma":0.0002014766,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9411941,"about_ca_topic_score_gemma":0.9873313,"domain_scores_codex":[0.9991556,0.00002224401,0.0002119614,0.000109629,0.0002830496,0.0002174893],"domain_scores_gemma":[0.9992642,0.00002099816,0.00009817015,0.0003914389,0.0001160417,0.0001091124],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[7.796856e-7,0.000009603048,0.930105,0.000007716812,0.0006905191,0.000003126538,0.05028043,0.000154789,0.00000134908,0.01663362,0.000540819,0.001572238],"study_design_scores_gemma":[0.0003333324,0.0000176085,0.8202217,0.00003328245,0.0005688007,5.48288e-7,0.04462781,0.0001489441,0.000009475521,0.0009989376,0.1327603,0.0002793253],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8354796,0.0002691247,0.0009207968,0.002960954,0.0004485988,0.0002545629,0.0002554585,0.00005119625,0.1593597],"genre_scores_gemma":[0.9992905,0.00002345991,0.00006696792,0.0002052236,0.00004573707,0.000002950692,0.00004957214,0.000002300036,0.0003133426],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1638108,"threshold_uncertainty_score":0.2058539,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06828416850590777,"score_gpt":0.3273240557045652,"score_spread":0.2590398871986574,"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."}}