{"meta":{"page":1,"per_page":50,"max_per_page":100,"total":7,"total_is_capped":false,"direct_labels_cover":0,"predictions_cover":7,"direct_label_status":"direct model label, unvalidated","prediction_status":"machine_predicted_unvalidated (Codex and Gemma teacher distillation)","score_status":"score_only:v0-immature-baseline (scores rank; they never assert a category)","snapshot":{"source":"OpenAlex, pinned release, all 482 partitions","release":"2026-06-24","frame_built":"2026-07-12","author_layer_release":"2026-06-26"},"query_hash":"49ef6bc5994e","filters":{"venue":"Journal of Statistics and Management Systems"}},"results":[{"id":"W2024201031","doi":"10.1080/09720510.2009.10701391","title":"Predictive densities from the Rayleigh Life Model under Type II censored samples","year":2009,"lang":"en","type":"article","venue":"Journal of Statistics and Management Systems","topic":"Statistical Distribution Estimation and Applications","field":"Mathematics","cited_by":3,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Western University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Rayleigh distribution; Predictive inference; Inference; Computer science; Bayesian inference; Statistics; Bayesian probability; Hyperparameter; Statistical inference; Hazard; Sample (material); Econometrics; Mathematics; Data mining; Frequentist inference; Machine learning; Probability density function; Artificial intelligence","authors":[{"name":"Hafiz M. R. Khan","is_ca":false},{"name":"Serge B. Provost","is_ca":true},{"name":"Amparo Amparo","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.07136402860229443,"gpt":0.3193674471612161,"spread":0.2480034185589216,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01879915,0.001027088,0.002158217,0.002262403,0.0006416992,0.002066101,0.003436714,0.002237316,0.006363622],"category_scores_gemma":[0.06342705,0.0008149457,0.001455624,0.001551458,0.003977964,0.004285658,0.002154856,0.003174288,0.0009282217],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001878928,"about_ca_system_score_gemma":0.0009737121,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00374164,"about_ca_topic_score_gemma":0.002469249,"domain_scores_codex":[0.9957448,0.002492169,0.0001470313,0.0005606926,0.0007854091,0.0002698271],"domain_scores_gemma":[0.9419852,0.04899406,0.002863451,0.00275637,0.002931763,0.0004691147],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0003104476,0.0001514703,0.01150121,0.0004223816,0.0001485316,0.0005946555,0.001086299,0.419747,0.001311425,0.5153223,0.003176249,0.04622803],"study_design_scores_gemma":[0.00003140092,0.0000746629,0.002819669,0.0001085039,0.00003935385,0.0002074967,0.0001779277,0.7958452,0.0006303087,0.1990058,0.001011639,0.00004801654],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.07223563,0.0008546184,0.9223325,0.0009981587,0.00004660408,0.0002236671,0.0004731763,0.0002995327,0.002536105],"genre_scores_gemma":[0.8746455,0.002088392,0.1115146,0.000475249,0.0002352912,0.0009223337,0.001481995,0.000145208,0.008491436],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01879915,"threshold_uncertainty_score":0.09942061,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3216151428","doi":"10.1080/09720510.2021.1974578","title":"On the convoluted gamma to length-biased inverse Gaussian distribution and application in financial modeling","year":2021,"lang":"en","type":"article","venue":"Journal of Statistics and Management Systems","topic":"Statistical Distribution Estimation and Applications","field":"Mathematics","cited_by":2,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Registered Nurses' Association of Ontario","funders":"","keywords":"Inverse Gaussian distribution; Normal-inverse Gaussian distribution; Inverse-gamma distribution; Gaussian; Autoregressive model; Gamma distribution; Generalized inverse Gaussian distribution; Inverse distribution; Variance-gamma distribution; Mathematics; Distribution (mathematics); Inverse; Unimodality; Statistical physics; Statistics; Applied mathematics; Probability distribution; Heavy-tailed distribution; Distribution fitting; Mathematical analysis; Gaussian process; Inverse-chi-squared distribution; Gaussian random field; Physics; Asymptotic distribution","authors":[{"name":"Shanoja Naik","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.04125756780613142,"gpt":0.3040332639932402,"spread":0.2627756961871087,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00363694,0.0008744431,0.0007858411,0.001646828,0.0006623773,0.001461376,0.001199684,0.001754165,0.002656062],"category_scores_gemma":[0.01580733,0.0003623211,0.001386902,0.00246105,0.002407881,0.002679112,0.001458396,0.002341198,0.0005494404],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001328033,"about_ca_system_score_gemma":0.001176909,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007389554,"about_ca_topic_score_gemma":0.004199448,"domain_scores_codex":[0.9987873,0.0005679984,0.00004076882,0.0002257797,0.0002566621,0.0001215129],"domain_scores_gemma":[0.9940605,0.004187595,0.0005641034,0.000360232,0.0006643023,0.0001633408],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00008538794,0.00006632526,0.008723635,0.0001629755,0.00009022119,0.0008974762,0.0005391761,0.2827614,0.002465253,0.645186,0.002750027,0.05627213],"study_design_scores_gemma":[0.00001085901,0.00006440291,0.002402214,0.00005530803,0.00003982245,0.0004474573,0.0001494333,0.7567417,0.0005707129,0.2352898,0.004179285,0.0000489506],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04365903,0.002255311,0.9484083,0.0009039668,0.000119027,0.00002986941,0.00008358457,0.0001489982,0.004391897],"genre_scores_gemma":[0.8783519,0.006267854,0.1049264,0.0008380791,0.0005975945,0.0001186497,0.0003101999,0.0001420789,0.008447316],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007389554,"threshold_uncertainty_score":0.01923424,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2903426484","doi":"10.1080/09720510.2018.1504644","title":"The decision model on voluntary review of quarterly consolidated financial statements","year":2018,"lang":"en","type":"article","venue":"Journal of Statistics and Management Systems","topic":"Auditing, Earnings Management, Governance","field":"Business, Management and Accounting","cited_by":2,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"","keywords":"Transparency (behavior); Corporate governance; Audit; Accounting; Business; External auditor; Voluntary disclosure; Turnover; Emerging markets; Quarter (Canadian coin); Finance; Economics; Internal audit; Political science; Management","authors":[{"name":"Chao-Wei Li","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.01193897752581718,"gpt":0.2622216509595185,"spread":0.2502826734337014,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01035327,0.001003615,0.002363225,0.001708459,0.0009129238,0.004215306,0.002552857,0.002672312,0.01415233],"category_scores_gemma":[0.02720377,0.001062479,0.001312391,0.001228627,0.001570096,0.00315117,0.001470991,0.003255286,0.001586699],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004032918,"about_ca_system_score_gemma":0.004049331,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03394767,"about_ca_topic_score_gemma":0.01725787,"domain_scores_codex":[0.9953532,0.001785864,0.000226951,0.001038105,0.000430577,0.001165194],"domain_scores_gemma":[0.9623515,0.02775415,0.005483506,0.0006507333,0.002177047,0.00158305],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002100737,0.000611292,0.03343546,0.0002472799,0.0002176488,0.001162342,0.0006742585,0.8520635,0.001583505,0.0681151,0.006365319,0.03342357],"study_design_scores_gemma":[0.0001401878,0.0001786723,0.005440498,0.00003177462,0.00006050904,0.0000942964,0.0001592121,0.9813106,0.0003079888,0.01126011,0.0009608651,0.00005525312],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8583034,0.001304255,0.1104307,0.007018876,0.0002540424,0.0007050632,0.002412814,0.0003394354,0.01923131],"genre_scores_gemma":[0.9768804,0.0004774613,0.004902548,0.0001547945,0.00008842901,0.0001747195,0.0007031143,0.00002965726,0.01658882],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03394767,"threshold_uncertainty_score":0.06750017,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2807788428","doi":"10.1080/09720510.2019.1649038","title":"Detecting intrusions in control systems : A rule of thumb, its justification and illustrations","year":2020,"lang":"en","type":"preprint","venue":"Journal of Statistics and Management Systems","topic":"Smart Grid Security and Resilience","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Western University","funders":"","keywords":"Rule of thumb; Intrusion detection system; Computer science; Rule-based system; Intrusion; Control (management); Data mining; Thumb; Computer security; Artificial intelligence; Algorithm; Geology","authors":[{"name":"Nadezhda Gribkova","is_ca":false},{"name":"Ričardas Zitikis","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.018297647042017,"gpt":0.2323837641661338,"spread":0.2140861171241168,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.03584711,0.001876943,0.002916919,0.004740752,0.002395784,0.007166238,0.004734075,0.007460005,0.001246925],"category_scores_gemma":[0.1150965,0.0009613668,0.002129104,0.00261357,0.01206547,0.005154676,0.003499198,0.007580405,0.001313969],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00152219,"about_ca_system_score_gemma":0.002933455,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002434131,"about_ca_topic_score_gemma":0.002056577,"domain_scores_codex":[0.9664918,0.01374373,0.004573659,0.003466403,0.01100845,0.000716048],"domain_scores_gemma":[0.8921553,0.07750542,0.004464361,0.01143295,0.01347973,0.0009622148],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004458216,0.0002842549,0.007327797,0.001237005,0.0003538558,0.001765187,0.0007239408,0.08548134,0.004198462,0.6860718,0.01823014,0.1938805],"study_design_scores_gemma":[0.0001108094,0.0002122168,0.0008315402,0.001204113,0.0001214121,0.001628357,0.0001804231,0.2364842,0.004688984,0.7338258,0.02055224,0.0001597932],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.007820812,0.002424894,0.9735267,0.007523113,0.0006913777,0.000216467,0.0001636648,0.0005635836,0.00706939],"genre_scores_gemma":[0.1578195,0.001425261,0.8361092,0.002284095,0.0007583718,0.000305434,0.0001089613,0.00008201312,0.001107138],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03584711,"threshold_uncertainty_score":0.1895799,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2111288576","doi":"10.1080/09720510.2002.10701055","title":"Generalized<i>b</i>-invex vector valued functions","year":2002,"lang":"en","type":"article","venue":"Journal of Statistics and Management Systems","topic":"Optimization and Variational Analysis","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Manitoba","funders":"Virginia Agricultural Experiment Station, Virginia Polytechnic Institute and State University","keywords":"Vector (molecular biology); Mathematics; Pure mathematics; Biology; Recombinant DNA","authors":[{"name":"C. R. Bector","is_ca":true},{"name":"Riccardo Cambini","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.02195350918094778,"gpt":0.2243346088997615,"spread":0.2023810997188137,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001328782,0.001009742,0.0005759897,0.001048661,0.0004514218,0.001749712,0.00075607,0.0009183682,0.005736678],"category_scores_gemma":[0.001948297,0.0002667036,0.0008022457,0.0005126191,0.00128962,0.001879586,0.001131804,0.001927585,0.0009825502],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007035416,"about_ca_system_score_gemma":0.0005416653,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009841082,"about_ca_topic_score_gemma":0.0004213597,"domain_scores_codex":[0.9994847,0.0001545785,0.00003181999,0.0001082144,0.0001392095,0.00008156792],"domain_scores_gemma":[0.9991517,0.0002156647,0.0001213795,0.0001001512,0.00029279,0.0001183531],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001206373,0.0000719079,0.001062434,0.0001480616,0.00003616253,0.0004273499,0.0002128284,0.0320649,0.009289303,0.9173965,0.003936939,0.03523283],"study_design_scores_gemma":[0.00002394374,0.0001724288,0.001850215,0.00009659804,0.00003238988,0.000998102,0.0002482331,0.4443267,0.005045715,0.5144688,0.032678,0.00005876992],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06900696,0.001270567,0.8879288,0.0008560264,0.000297409,0.00004664695,0.0002143097,0.0002253688,0.04015379],"genre_scores_gemma":[0.796822,0.003031344,0.1409725,0.0009663901,0.0005651194,0.0002762835,0.0006672369,0.0002876853,0.05641145],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005736678,"threshold_uncertainty_score":0.01919109,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1992492447","doi":"10.1080/09720510.2009.10701386","title":"An analytical approach on estimation of cure rate from mixture model based on Type 2 censoring","year":2009,"lang":"en","type":"article","venue":"Journal of Statistics and Management Systems","topic":"Statistical Distribution Estimation and Applications","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Concordia University","funders":"","keywords":"Censoring (clinical trials); Estimation; Statistics; Econometrics; Mathematics; Computer science; Applied mathematics; Economics","authors":[{"name":"Md. Tamez Uddin","is_ca":false},{"name":"Arusharka Sen","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.05775459837457547,"gpt":0.3500204306731592,"spread":0.2922658322985837,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009050032,0.00096113,0.00182523,0.002702703,0.0004455505,0.001578886,0.002540193,0.001974976,0.002877445],"category_scores_gemma":[0.0355874,0.001086927,0.002242895,0.001770945,0.001296342,0.003303857,0.001748606,0.002422364,0.0005235565],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001328783,"about_ca_system_score_gemma":0.001036231,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002218019,"about_ca_topic_score_gemma":0.00116721,"domain_scores_codex":[0.9958509,0.002248481,0.0001470846,0.0005075653,0.000958089,0.0002878494],"domain_scores_gemma":[0.9862604,0.01079247,0.001029212,0.0006484762,0.001091679,0.000177791],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001393524,0.00007961614,0.007262003,0.0004727835,0.0002639696,0.00054344,0.0006176421,0.6486701,0.004313143,0.2680328,0.002222263,0.06738286],"study_design_scores_gemma":[0.000006974101,0.00002600536,0.0006400192,0.00004137746,0.00003959078,0.0001857939,0.00002467029,0.9695967,0.0005265633,0.02793273,0.00095254,0.00002698688],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.004658678,0.0003910528,0.9940438,0.0001697754,0.00002590102,0.00002437421,0.00002447699,0.00007651208,0.0005854109],"genre_scores_gemma":[0.6261405,0.003501597,0.3595353,0.0003873982,0.0003946516,0.0004818947,0.0004021811,0.0002408733,0.008915492],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.009050032,"threshold_uncertainty_score":0.0478617,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4416620652","doi":"10.47974/jsms-1509","title":"Empathy among management students : An assessment scale-based study of university students in Gujarat","year":2025,"lang":"","type":"article","venue":"Journal of Statistics and Management Systems","topic":"Emotional Intelligence and Performance","field":"Psychology","cited_by":0,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"","keywords":"Empathy; Confirmatory factor analysis; Exploratory factor analysis; Psychological resilience; Reliability (semiconductor); Construct (python library); Emotional intelligence","authors":[{"name":"Jayendra P. Siddhapura","is_ca":false},{"name":"Ranjana Dureja","is_ca":false},{"name":"Priyanka K Suchak","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.02536040724257485,"gpt":0.3868487088946135,"spread":0.3614883016520386,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000754762,0.0002865124,0.0003319049,0.001189368,0.001695126,0.0009360996,0.0003836131,0.0006724246,0.0007991452],"category_scores_gemma":[0.001578427,0.0002646793,0.0004283585,0.000903026,0.0007811665,0.0003763045,0.0008840549,0.0006576439,0.0002609364],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001140682,"about_ca_system_score_gemma":0.0009597254,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00903939,"about_ca_topic_score_gemma":0.0181584,"domain_scores_codex":[0.9994635,0.0001376269,0.00004748304,0.00006186285,0.0001070502,0.0001825273],"domain_scores_gemma":[0.9990656,0.0001058929,0.0003014426,0.00003280303,0.0001504686,0.0003439112],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00007226602,0.0006480028,0.9416894,0.00006620691,0.00002608856,0.0006943604,0.04477283,0.00005015154,0.002384234,0.00009853452,0.0002354453,0.009262551],"study_design_scores_gemma":[0.00000398479,0.0004000088,0.9738283,0.00001755612,0.00001075375,0.0003414605,0.02444291,0.00009123802,0.0001721158,0.00002395144,0.00065663,0.00001112863],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9997912,0.00002086839,0.00001368822,0.00002840196,0.00000110767,0.000006947289,0.00000930048,5.556842e-7,0.0001279795],"genre_scores_gemma":[0.9996306,0.00004369294,0.00006730814,0.00002835794,0.000001920439,0.00001509196,0.00002451343,5.085033e-7,0.0001878787],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00903939,"threshold_uncertainty_score":0.0179736,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null}]}