{"meta":{"query_hash":"7712aebac180","filters":{"venue":"Информационные и математические технологии в науке и управлении"},"cohort_total":8,"direct_labels_cover":0,"predictions_cover":8,"exported":8,"export_cap":100000,"truncated":false,"label_status":"direct model label, unvalidated","prediction_status":"machine_predicted_unvalidated (Codex and Gemma teacher distillation)","score_status":"score_only:v0-immature-baseline","snapshot":{"source":"OpenAlex, pinned release, all 482 partitions","release":"2026-06-24","frame_built":"2026-07-12"},"permalink":"https://metacan.xera.ac/q/7712aebac180","api":"https://metacan.xera.ac/api/v1/cohort?venue=%D0%98%D0%BD%D1%84%D0%BE%D1%80%D0%BC%D0%B0%D1%86%D0%B8%D0%BE%D0%BD%D0%BD%D1%8B%D0%B5+%D0%B8+%D0%BC%D0%B0%D1%82%D0%B5%D0%BC%D0%B0%D1%82%D0%B8%D1%87%D0%B5%D1%81%D0%BA%D0%B8%D0%B5+%D1%82%D0%B5%D1%85%D0%BD%D0%BE%D0%BB%D0%BE%D0%B3%D0%B8%D0%B8+%D0%B2+%D0%BD%D0%B0%D1%83%D0%BA%D0%B5+%D0%B8+%D1%83%D0%BF%D1%80%D0%B0%D0%B2%D0%BB%D0%B5%D0%BD%D0%B8%D0%B8"},"results":[{"id":"W3113966686","doi":"10.38028/esi.2020.20.4.015","title":"ARCHITECTURE OF THE INTELLECTUAL INFORMATION SYSTEM TO SUPPORT EXPERT DECISIONS ON STRATEGIC INNOVATIVE ENERGY DEVELOPMENT","year":2020,"lang":"ru","type":"article","venue":"Информационные и математические технологии в науке и управлении","topic":"Economic and Technological Developments in Russia","field":"Social Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Component (thermodynamics); Architecture; Expert system; Computer science; Information system; Big data; Knowledge management; Systems architecture; Process management; Data science; Systems engineering; Engineering management; Engineering; Artificial intelligence; Data mining","score_opus":0.06547297095835619,"score_gpt":0.2731124180709148,"score_spread":0.2076394471125586,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3113966686","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.044407584,0.0009832107,0.87024254,0.0044602323,0.00028471576,0.0011458835,0.0015219453,0.012029818,0.06492408],"genre_scores_gemma":[0.36294788,0.0011330497,0.6092521,0.0004052601,0.00017996912,0.00066507765,0.004056895,0.000492554,0.020867156],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9973073,0.0007609747,0.00038271616,0.00047264728,0.00081563776,0.00026071264],"domain_scores_gemma":[0.9964211,0.00079986564,0.0003103453,0.0010615214,0.0009960585,0.00041108148],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0040884893,0.0005704209,0.0007585829,0.005099238,0.0019500739,0.009572785,0.002379383,0.0020436214,0.0067445296],"category_scores_gemma":[0.006334514,0.0005553079,0.0009091274,0.0042431667,0.0014748612,0.0064229793,0.0040822187,0.0012904371,0.0037818358],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00059380254,0.0007658134,0.015807834,0.0008992981,0.00049046654,0.0019085333,0.0052757137,0.058149446,0.020070694,0.3601742,0.02674859,0.5091156],"study_design_scores_gemma":[0.00019493052,0.00054065016,0.009181495,0.0006691021,0.00071507186,0.0017037608,0.0028302984,0.32309496,0.028605169,0.21375053,0.41840515,0.00030894743],"about_ca_topic_score_codex":0.0057194605,"about_ca_topic_score_gemma":0.004369006,"teacher_disagreement_score":0.009572785,"about_ca_system_score_codex":0.0019361988,"about_ca_system_score_gemma":0.008129925,"threshold_uncertainty_score":0.022562742},"labels":[],"label_agreement":null},{"id":"W3157127218","doi":"10.38028/esi.2021.21.1.005","title":"NUMERICAL ESTIMATION OF CRITICAL CONDITIONS IN THERMAL EXPLOSION PROBLEM FOR A MEDIUM WITH FLUCTUATIONS OF REACTIVITY","year":2021,"lang":"ru","type":"article","venue":"Информационные и математические технологии в науке и управлении","topic":"Material Science and Thermodynamics","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Siberian Branch, Russian Academy of Sciences; Ministère de l'Économie, de la Science et de l'Innovation - Québec","keywords":"Inflection point; Thermodynamics; Reactivity (psychology); Dispersion (optics); Thermal; Critical point (mathematics); Function (biology); Distribution function; Distribution (mathematics); Physics; Mechanics; Mathematics; Mathematical analysis; Quantum mechanics; Geometry","score_opus":0.012418082279916571,"score_gpt":0.2691964242278125,"score_spread":0.2567783419478959,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3157127218","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.42364085,0.0020344213,0.54933184,0.0020118158,0.0002005478,0.00017248695,0.00029649955,0.00025703962,0.022054503],"genre_scores_gemma":[0.96893233,0.00043930032,0.02651017,0.00005745295,0.00003819422,0.0001107554,0.0001129013,0.000040864838,0.0037580598],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998266,0.00007852286,0.0000076256524,0.000024631265,0.000026163145,0.000036406538],"domain_scores_gemma":[0.9978823,0.0016139542,0.00018230909,0.00003036069,0.000174989,0.00011601274],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00087065855,0.00065448484,0.0007879385,0.0008101098,0.00058164634,0.001450892,0.00077985047,0.0018037063,0.0016087536],"category_scores_gemma":[0.0037124502,0.00041651752,0.0006612713,0.00044772515,0.0015720003,0.0008961056,0.001091175,0.0012234098,0.00009486296],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000083432176,0.000022573107,0.0011005998,0.000087725246,0.000019445673,0.00015430318,0.00004834928,0.9831381,0.001379289,0.0120122405,0.0002628275,0.0016910976],"study_design_scores_gemma":[0.000004198149,0.000008917536,0.00008675748,0.0000040008276,0.0000021641297,0.000005011964,0.000014040497,0.99861646,0.00013800012,0.0010622144,0.000054541422,0.000003638507],"about_ca_topic_score_codex":0.010976487,"about_ca_topic_score_gemma":0.004602465,"teacher_disagreement_score":0.010976487,"about_ca_system_score_codex":0.0010029959,"about_ca_system_score_gemma":0.0011668208,"threshold_uncertainty_score":0.021825194},"labels":[],"label_agreement":null},{"id":"W3215086644","doi":"10.38028/esi.2021.23.3.002","title":"COMPONENTS OF THE ONTOLOGICAL KNOWLEDGE SPACE FOR ASSESSING THE IMPACT OF ENERGY ON THE QUALITY OF LIFE OF THE POPULATION","year":2021,"lang":"ru","type":"article","venue":"Информационные и математические технологии в науке и управлении","topic":"Arctic and Russian Policy Studies","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Siberian Branch, Russian Academy of Sciences; Russian Foundation for Basic Research; Ministère de l'Économie, de la Science et de l'Innovation - Québec","keywords":"Ontology; Component (thermodynamics); Space (punctuation); Population; Quality (philosophy); Natural (archaeology); Quality of life (healthcare); Energy (signal processing); Environmental quality; Computer science; Environmental resource management; Ecology; Geography; Sociology; Psychology; Environmental science; Epistemology; Mathematics; Biology","score_opus":0.17068979910549528,"score_gpt":0.4500292782642931,"score_spread":0.27933947915879787,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3215086644","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.25743258,0.0025329601,0.5838549,0.007335359,0.00032933214,0.0016414209,0.013452373,0.0009566474,0.13246445],"genre_scores_gemma":[0.7736192,0.0008755899,0.2163067,0.00020592942,0.000034229426,0.0007709502,0.0049375487,0.000058379457,0.0031915365],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9949732,0.0018961452,0.0005402137,0.00051985896,0.001668202,0.00040231858],"domain_scores_gemma":[0.9939167,0.0030191094,0.00059042725,0.00070270343,0.0013876504,0.0003834699],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004197133,0.0008264592,0.000614657,0.01092395,0.00224236,0.008713505,0.0013876586,0.0012693348,0.0050773816],"category_scores_gemma":[0.016138867,0.00038138335,0.0025400876,0.0093976045,0.0025547151,0.0065354556,0.0048169224,0.0013771042,0.00071245217],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003323861,0.00035455276,0.06258693,0.0010639844,0.00062302186,0.0007960566,0.01596666,0.015661212,0.0029115677,0.6324606,0.007198362,0.26004472],"study_design_scores_gemma":[0.00007321435,0.00020692899,0.06440223,0.0017802477,0.0010654469,0.0009389767,0.04849181,0.10023872,0.0038238834,0.6872018,0.091493554,0.00028320143],"about_ca_topic_score_codex":0.021968259,"about_ca_topic_score_gemma":0.01779491,"teacher_disagreement_score":0.021968259,"about_ca_system_score_codex":0.0036435628,"about_ca_system_score_gemma":0.005948971,"threshold_uncertainty_score":0.043680727},"labels":[],"label_agreement":null},{"id":"W3216570654","doi":"10.38028/esi.2021.23.3.001","title":"QUALITY OF LIFE AS A FACTOR FOR INTEGRATION OF RESILIENCE RESEARCH OF ENERGY, SOCIO-ECOLOGICAL AND SOCIO-ECONOMIC SYSTEMS","year":2021,"lang":"ru","type":"article","venue":"Информационные и математические технологии в науке и управлении","topic":"Global Energy and Sustainability Research","field":"Energy","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Siberian Branch, Russian Academy of Sciences; Russian Foundation for Basic Research; Ministère de l'Économie, de la Science et de l'Innovation - Québec","keywords":"Resilience (materials science); Quality (philosophy); Environmental resource management; Psychological resilience; Ecological systems theory; Quality of life (healthcare); Energy (signal processing); Socio-ecological system; Cognition; Ecology; Psychology; Computer science; Environmental science; Social psychology; Mathematics; Biology","score_opus":0.10781518141551236,"score_gpt":0.413713584430051,"score_spread":0.30589840301453863,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3216570654","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.44341424,0.0445013,0.25295827,0.024456184,0.0015179529,0.00063002063,0.00088131806,0.00021545624,0.23142521],"genre_scores_gemma":[0.97520137,0.004012372,0.018398495,0.00018384041,0.00012482307,0.00013731128,0.000088830515,0.000018312794,0.0018345913],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9988778,0.0006255775,0.000057684923,0.000109131535,0.00024502337,0.00008472741],"domain_scores_gemma":[0.99700975,0.0018372778,0.0004386654,0.00015812268,0.0003179669,0.00023825407],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0019042458,0.00047898394,0.00048114886,0.0027033763,0.0009508052,0.0027530089,0.00048196246,0.0007042774,0.0048155007],"category_scores_gemma":[0.0045424555,0.00010983487,0.0007954198,0.0025810872,0.003702685,0.003270409,0.0016560357,0.0013737711,0.0002802575],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000845981,0.0001811277,0.04699077,0.0009632289,0.0001649163,0.00051092636,0.0071951766,0.0058825663,0.0013210692,0.7763234,0.0034462677,0.15693606],"study_design_scores_gemma":[0.000019766447,0.000660512,0.13293341,0.0021118692,0.00037760957,0.0012153379,0.023648258,0.01725426,0.001462833,0.746035,0.07408868,0.00019246813],"about_ca_topic_score_codex":0.0022200022,"about_ca_topic_score_gemma":0.0022293017,"teacher_disagreement_score":0.0048155007,"about_ca_system_score_codex":0.0021146566,"about_ca_system_score_gemma":0.0015921762,"threshold_uncertainty_score":0.016109407},"labels":[],"label_agreement":null},{"id":"W4205540067","doi":"10.38028/esi.2021.24.4.009","title":"REENGINEERING TECHNIQUE ADAPTATION OF LEGACY SOFTWARE SYSTEMS","year":2022,"lang":"ru","type":"article","venue":"Информационные и математические технологии в науке и управлении","topic":"Engineering Education and Technology","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Siberian Branch, Russian Academy of Sciences; Russian Foundation for Basic Research; Ministère de l'Économie, de la Science et de l'Innovation - Québec","keywords":"Business process reengineering; Computer science; Adaptation (eye); Legacy system; Software system; Process management; Software; Software engineering; Systems engineering; Engineering; Manufacturing engineering; Operating system","score_opus":0.015239728553331649,"score_gpt":0.22192257312098992,"score_spread":0.20668284456765829,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4205540067","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.23951112,0.0036720035,0.70516765,0.00049183646,0.0002685979,0.00035522203,0.00011845032,0.00400071,0.046414495],"genre_scores_gemma":[0.7407004,0.002445836,0.23474894,0.00010401967,0.00010375267,0.00014636328,0.00026572312,0.00038613201,0.021098832],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.998611,0.00037954407,0.000099642086,0.00024462433,0.00055537693,0.000109910274],"domain_scores_gemma":[0.9982784,0.00043961118,0.00019018678,0.00074366754,0.0002840119,0.000064181215],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010343884,0.00037085492,0.00029654516,0.0012216478,0.0005567794,0.0016644503,0.00096098124,0.0007666474,0.0018832907],"category_scores_gemma":[0.0035889426,0.00023220324,0.0005800533,0.0010705481,0.00042401307,0.001508904,0.0013077044,0.0007085141,0.0009622675],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014007378,0.00021912053,0.005406886,0.00039649723,0.00008769992,0.0010628296,0.0031037885,0.014526762,0.06196897,0.026088001,0.001976249,0.8850232],"study_design_scores_gemma":[0.00011246189,0.0012078922,0.05348008,0.0006120876,0.00055891584,0.009040609,0.0033921027,0.31355113,0.18719468,0.059910048,0.37061465,0.0003253752],"about_ca_topic_score_codex":0.0013942344,"about_ca_topic_score_gemma":0.0013506331,"teacher_disagreement_score":0.0018832907,"about_ca_system_score_codex":0.00034178197,"about_ca_system_score_gemma":0.00077396515,"threshold_uncertainty_score":0.0063002706},"labels":[],"label_agreement":null},{"id":"W4206451096","doi":"10.38028/esi.2021.24.4.001","title":"MODERN STAGE OF ARTIFICIAL INTELLIGENCE (AI) DEVELOPMENT AND APPLICATION OF AI METHODS AND SYSTEMS IN POWER ENGINEERING","year":2022,"lang":"ru","type":"article","venue":"Информационные и математические технологии в науке и управлении","topic":"Economic and Technological Systems Analysis","field":"Business, Management and Accounting","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Siberian Branch, Russian Academy of Sciences; Russian Foundation for Basic Research; Ministère de l'Économie, de la Science et de l'Innovation - Québec","keywords":"Applications of artificial intelligence; Artificial intelligence; Computer science; Ontology; Trustworthiness; Computer security","score_opus":0.022683722509268724,"score_gpt":0.2608125468587086,"score_spread":0.23812882434943985,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4206451096","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.027306909,0.08777637,0.15995818,0.039290603,0.0026440034,0.00022711497,0.00042788824,0.00040047918,0.68196845],"genre_scores_gemma":[0.63440067,0.08386502,0.14493613,0.0050354637,0.0026043816,0.00047182225,0.0005027925,0.00032736058,0.12785631],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9965402,0.0014362423,0.00022104547,0.00043253822,0.001179464,0.00019054419],"domain_scores_gemma":[0.99780124,0.0008770234,0.00018654947,0.0003215889,0.0006698999,0.00014366525],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0037621972,0.000605288,0.0003985484,0.0020035487,0.0016472584,0.0069687106,0.0009813574,0.0023147222,0.0064939517],"category_scores_gemma":[0.0037961989,0.00039996067,0.00058108004,0.0023972178,0.008526394,0.0061364486,0.0024522662,0.003585568,0.0027159953],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000025001624,0.000027310052,0.0005455519,0.00028557313,0.000015825482,0.000085289445,0.0013406817,0.00077983504,0.0009448657,0.9316469,0.0063064764,0.057996657],"study_design_scores_gemma":[0.000017199438,0.000090789305,0.0022052831,0.00055538287,0.000020761643,0.00032876022,0.0010174375,0.0024303917,0.0020479618,0.39432833,0.5969079,0.000049918148],"about_ca_topic_score_codex":0.004498431,"about_ca_topic_score_gemma":0.0032807854,"teacher_disagreement_score":0.0069687106,"about_ca_system_score_codex":0.0051237196,"about_ca_system_score_gemma":0.005111801,"threshold_uncertainty_score":0.037175357},"labels":[],"label_agreement":null},{"id":"W4206653685","doi":"10.38028/esi.2021.24.4.010","title":"DESIGN AND DEVELOPMENT OF INSTRUMENTAL TOOLS FOR SEMANTIC ANALYSIS OF BIG DATA SCIENTIFIC AND TECHNOLOGICAL SOLUTIONS IN THE FIELD OF ENERGY","year":2022,"lang":"ru","type":"article","venue":"Информационные и математические технологии в науке и управлении","topic":"Arctic and Russian Policy Studies","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"Siberian Branch, Russian Academy of Sciences; Russian Foundation for Basic Research","keywords":"Computer science; Python (programming language); Field (mathematics); Data science; Ontology; Information retrieval; World Wide Web; Programming language","score_opus":0.1843178252219632,"score_gpt":0.3476245022274727,"score_spread":0.16330667700550952,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4206653685","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0034460314,0.00020770122,0.9515761,0.0007809119,0.00015660745,0.0006670152,0.0020274215,0.034469917,0.0066682636],"genre_scores_gemma":[0.048356682,0.00038209255,0.9325988,0.00044833904,0.000047430396,0.0013061123,0.006677146,0.004695455,0.0054879286],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9938706,0.0020649985,0.0008330747,0.00091697834,0.0018999898,0.00041436867],"domain_scores_gemma":[0.9907171,0.004407194,0.00053831405,0.0020088954,0.0017304902,0.00059808075],"candidate_categories":["bibliometrics"],"consensus_categories":[],"category_scores_codex":[0.008859912,0.0016604087,0.0009812677,0.0042298557,0.0018545381,0.007814461,0.0035174633,0.0020260408,0.009422848],"category_scores_gemma":[0.021286944,0.0012566221,0.0031956832,0.002497609,0.0024446272,0.009932694,0.007324352,0.0033862512,0.006104912],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00097219495,0.0007027861,0.0067339772,0.005308524,0.0005345767,0.0015856979,0.008454052,0.026240118,0.035182472,0.45447546,0.0777466,0.3820636],"study_design_scores_gemma":[0.00019718883,0.00020001808,0.0022058727,0.0008935442,0.0002551538,0.00062498474,0.002832575,0.22719674,0.05157733,0.25542384,0.4583775,0.00021524743],"about_ca_topic_score_codex":0.0039438666,"about_ca_topic_score_gemma":0.0049995016,"teacher_disagreement_score":0.99577016,"about_ca_system_score_codex":0.0018440869,"about_ca_system_score_gemma":0.006846689,"threshold_uncertainty_score":0.046856284},"labels":[],"label_agreement":null},{"id":"W4285412837","doi":"10.38028/esi.2022.26.2.012","title":"Ontological analysis of the interrelationships of energy and socio-ecological systems","year":2022,"lang":"ru","type":"article","venue":"Информационные и математические технологии в науке и управлении","topic":"Global Energy and Sustainability Research","field":"Energy","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Siberian Branch, Russian Academy of Sciences; Russian Foundation for Basic Research; Ministère de l'Économie, de la Science et de l'Innovation - Québec","keywords":"Ecology; Energy (signal processing); Geography; Environmental resource management; Biology; Environmental science; Mathematics","score_opus":0.03214474208330066,"score_gpt":0.28337732147233724,"score_spread":0.2512325793890366,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4285412837","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.14367732,0.00766625,0.48223066,0.019767629,0.00052016176,0.00023917343,0.0012966305,0.00017916782,0.3444229],"genre_scores_gemma":[0.91383594,0.0024236557,0.07609917,0.00046469615,0.00010814782,0.00015543151,0.000802078,0.00005309191,0.006057819],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9982199,0.0010235299,0.00010909648,0.00013686648,0.00038316322,0.00012742876],"domain_scores_gemma":[0.99770445,0.0012476068,0.00016237392,0.00037934494,0.00035593024,0.00015033784],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0027503541,0.0003217833,0.00032551496,0.0033094864,0.0027735876,0.006098103,0.0008610631,0.0009041508,0.002729492],"category_scores_gemma":[0.004657006,0.00025258353,0.0008677556,0.00425608,0.0070865373,0.008247159,0.0026806262,0.0017878889,0.00030087182],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000004759073,0.000007881189,0.00051097263,0.000026361784,0.0000086245645,0.00005485456,0.0015037118,0.0005087903,0.00011575603,0.99264973,0.00046970163,0.004138808],"study_design_scores_gemma":[0.0000050493045,0.000006544607,0.0014562488,0.00012303698,0.000032097767,0.00013293895,0.005612522,0.0070547513,0.00023805868,0.9510447,0.03428089,0.000013040379],"about_ca_topic_score_codex":0.009266345,"about_ca_topic_score_gemma":0.010150308,"teacher_disagreement_score":0.009266345,"about_ca_system_score_codex":0.0033915236,"about_ca_system_score_gemma":0.0031465702,"threshold_uncertainty_score":0.0246073},"labels":[],"label_agreement":null}]}