{"id":"W4399784636","doi":"10.25518/0037-9565.11913","title":"A Year-long Representation of the ILMT Observations in Different Coordinate Systems","year":2024,"lang":"en","type":"article","venue":"Bulletin de la Société Royale des Sciences de Liège","topic":"GNSS positioning and interference","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; Université Laval","funders":"Natural Sciences and Engineering Research Council of Canada; Service Public de Wallonie; Université de Liège; Belgian Federal Science Policy Office; Fonds De La Recherche Scientifique - FNRS; Department of Science and Technology, Ministry of Science and Technology, India; York University","keywords":"Representation (politics); Coordinate system; Geology; Computer science; Mathematics; Geodesy; Artificial intelligence; Political science","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0003552175,0.00008015251,0.0001031855,0.0000566432,0.0001204256,0.0001763237,0.0002490572,0.00005843996,0.00005659413],"category_scores_gemma":[0.00006551219,0.0000599587,0.00005729243,0.0003464282,0.0003712955,0.0000492613,0.00003977613,0.0001556019,0.00001140832],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001456277,"about_ca_system_score_gemma":0.00003409478,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003703791,"about_ca_topic_score_gemma":0.00001937114,"domain_scores_codex":[0.9992174,0.000131558,0.0001763579,0.000136811,0.0001452468,0.0001926104],"domain_scores_gemma":[0.9995151,0.0003040789,0.00002336812,0.0001102088,0.00002240436,0.0000248267],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.00001245734,0.0001582922,0.3780858,0.001266767,0.0000950936,0.0000245774,0.01328753,0.4626139,0.01941169,0.06892113,0.05296192,0.003160777],"study_design_scores_gemma":[0.0002991181,0.00007716367,0.5105951,0.001816312,0.00003819847,0.00003833111,0.002663675,0.4680214,0.008176846,0.004707681,0.003263872,0.0003023053],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9772098,0.000881239,0.003070666,0.0003639702,0.000375839,0.0001107475,0.000007582603,0.0001110628,0.01786907],"genre_scores_gemma":[0.998551,0.0000406236,0.0004261853,0.00002263079,0.00004600332,0.0000426327,0.000001357762,0.000009569229,0.0008600375],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1325092,"threshold_uncertainty_score":0.2445045,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0383563808998162,"score_gpt":0.3022545885721297,"score_spread":0.2638982076723135,"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."}}