{"id":"W7011320597","doi":"","title":"Magnetic Resonance and its Applications. Abstracts book. Saint Petersburg State University. April 23-29, 2017","year":2017,"lang":"en","type":"book","venue":"Research Repository Saint Petersburg State University (Saint Petersburg State University)","topic":"Advanced Scientific Techniques and Applications","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Gebze Teknik Üniversitesi; Natural Sciences and Engineering Research Council of Canada; Kazan Federal University; Bilim, Sanayi ve Teknoloji Bakanliği; Russian Science Foundation; Centre National de la Recherche Scientifique; Russian Foundation for Basic Research; German-Russian Interdisciplinary Science Center","keywords":"Saint petersburg; St petersburg; State (computer science); Magnetic resonance imaging; Resonance (particle physics); Electromagnetic radiation; Object (grammar); Reputation","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":["metaepi_narrow","sts","research_integrity"],"consensus_categories":["metaepi_narrow","sts"],"category_scores_codex":[0.001866908,0.001603203,0.001422761,0.002273281,0.005530287,0.0006869652,0.004917215,0.0007289613,0.0003659771],"category_scores_gemma":[0.0001077653,0.002040395,0.0007359216,0.001222492,0.004782233,0.002561092,0.004779034,0.003184115,0.0007462422],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01718708,"about_ca_system_score_gemma":0.001108972,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004240428,"about_ca_topic_score_gemma":0.000610654,"domain_scores_codex":[0.9881911,0.001016766,0.001015308,0.004264226,0.002626604,0.002886034],"domain_scores_gemma":[0.9910777,0.0008228533,0.001535073,0.003622429,0.0008028426,0.00213909],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.01087067,0.00378953,0.0027992,0.003518624,0.002470467,0.1042874,0.01154421,0.01162281,0.05107231,0.04592693,0.5515059,0.200592],"study_design_scores_gemma":[0.001737815,0.0005750254,0.00156533,0.000525392,0.0002197444,0.000163279,0.001327192,0.0007376024,0.0006994609,0.00119847,0.9891769,0.002073831],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.1642932,0.006262464,0.02242433,0.002732403,0.001744453,0.02128114,0.00869856,0.003469928,0.7690935],"genre_scores_gemma":[0.01334631,0.01117906,0.001715458,0.00006734668,0.0001458367,0.00001059616,0.0003837527,0.0002023113,0.9729493],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.4376709,"threshold_uncertainty_score":0.9996716,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02064510939219621,"score_gpt":0.2478998868042807,"score_spread":0.2272547774120845,"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."}}