{"id":"W2024279334","doi":"10.1002/mop.21947","title":"Orthogonal projection sampling method used in reconstruction of incomplete data field","year":2006,"lang":"en","type":"article","venue":"Microwave and Optical Technology Letters","topic":"Optical Systems and Laser Technology","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Polytechnique Montréal","keywords":"Sampling (signal processing); Projection (relational algebra); Orthographic projection; Computer science; Field (mathematics); Iterative reconstruction; Range (aeronautics); Algorithm; Artificial intelligence; Computer vision; Mathematics; Engineering","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001724703,0.0001193972,0.0002586038,0.0003329745,0.00002528402,0.000009862819,0.0001694342,0.0003122896,0.000004702767],"category_scores_gemma":[0.00003839466,0.0001178149,0.00002184358,0.0003425027,0.0001479548,0.00008087657,0.0001078232,0.0003450978,0.000002260821],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002563002,"about_ca_system_score_gemma":0.000004969234,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005613875,"about_ca_topic_score_gemma":0.0001842283,"domain_scores_codex":[0.9990984,0.00001435143,0.0003376725,0.0002629162,0.0000529313,0.0002337676],"domain_scores_gemma":[0.9995488,0.00009478607,0.00003228022,0.00029456,0.0000125582,0.0000170032],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000008573676,0.00001839019,0.01639077,0.00006176542,0.00002126977,0.000009453559,0.000006178389,0.0001387256,0.9140924,0.01367887,0.00007964208,0.05549392],"study_design_scores_gemma":[0.00255832,0.0003448807,0.01694834,0.0003880344,0.0001103772,0.001136136,0.0004329602,0.06729529,0.8861284,0.018124,0.005401889,0.001131442],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8459913,0.00009650225,0.1516574,0.001555148,0.00009474186,0.0001272658,0.000007108209,0.0001980227,0.0002724737],"genre_scores_gemma":[0.8890359,0.00001021408,0.1108364,0.00004851219,0.00003311941,0.000009587086,0.00001235934,0.0000120824,0.000001860522],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06715656,"threshold_uncertainty_score":0.4804353,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02023343299655794,"score_gpt":0.2525024043602591,"score_spread":0.2322689713637011,"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."}}