{"id":"W15345085","doi":"10.1186/1472-6874-4-s1-s22","title":"Решение краевой задачи динамической геодезии типа Дирихле методом вейвлет-анализа","year":2011,"lang":"en","type":"article","venue":"Interexpo GEO-Siberia","topic":"Elasticity and Wave Propagation","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science","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":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0002431368,0.0004611516,0.0004099872,0.0002116688,0.0001264117,0.00009972931,0.0005191244,0.0003023334,0.002885196],"category_scores_gemma":[0.00009448718,0.0004729095,0.0001905845,0.0002629483,0.0001197989,0.0004536992,0.0001541606,0.0005442959,0.003183973],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001429787,"about_ca_system_score_gemma":0.00003039146,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002157387,"about_ca_topic_score_gemma":0.0001595944,"domain_scores_codex":[0.9978575,0.00006974545,0.0006292845,0.0004466142,0.0002831707,0.0007136631],"domain_scores_gemma":[0.9988545,0.00008561567,0.000101074,0.0005917769,0.000124679,0.0002423923],"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":[0.001415598,0.002345152,0.02142395,0.003307922,0.00333634,0.0008797089,0.06805596,0.006300428,0.4314208,0.05820284,0.1771844,0.2261269],"study_design_scores_gemma":[0.005442471,0.001748321,0.0690479,0.001873211,0.0005149578,0.0004148634,0.002020354,0.0614999,0.6290137,0.04025343,0.1823309,0.005840051],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8558067,0.0003955236,0.03374396,0.0001314856,0.003845087,0.0004915972,0.00006286766,0.001450349,0.1040724],"genre_scores_gemma":[0.9948471,0.00007379645,0.002847562,0.0002433079,0.0004675014,0.00006052464,0.00006306971,0.0001236214,0.001273494],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2202869,"threshold_uncertainty_score":0.9997723,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02771240385542103,"score_gpt":0.1647616501656699,"score_spread":0.1370492463102488,"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."}}