{"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":"f2dd7f9a2141","filters":{"venue":"2022 IEEE 31st International Symposium on Industrial Electronics (ISIE)"}},"results":[{"id":"W4287882695","doi":"10.1109/isie51582.2022.9831670","title":"Formation Shaping Control for Multi-Agent Systems with Obstacle Avoidance and Dynamic Leader Selection","year":2022,"lang":"en","type":"article","venue":"2022 IEEE 31st International Symposium on Industrial Electronics (ISIE)","topic":"Distributed Control Multi-Agent Systems","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Dalhousie University","funders":"","keywords":"Collision avoidance; Obstacle avoidance; Obstacle; Computer science; Mobile robot; Process (computing); Collision; Controller (irrigation); Control theory (sociology); Displacement (psychology); Robot; Trajectory; Control engineering; Control (management); Real-time computing; Artificial intelligence; Engineering","authors":[{"name":"Ryan Adderson","is_ca":true},{"name":"Ya‐Jun Pan","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.04161474487076511,"gpt":0.2659374443167727,"spread":0.2243226994460076,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006566225,0.0007373583,0.0005916709,0.0003057162,0.0005215869,0.0007390692,0.001094852,0.0006152736,0.001211649],"category_scores_gemma":[0.001283493,0.0002668516,0.0004338467,0.0003154748,0.0009038359,0.0005984572,0.001018028,0.0007658088,0.0002434911],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005579551,"about_ca_system_score_gemma":0.000664465,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002461915,"about_ca_topic_score_gemma":0.002025241,"domain_scores_codex":[0.9996243,0.00009969725,0.00001796557,0.00007883566,0.0001307245,0.00004851032],"domain_scores_gemma":[0.9995019,0.0001867805,0.0001308473,0.00004471208,0.0000989563,0.00003668114],"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":[0.00005056224,0.0000396284,0.0002581077,0.00009084155,0.00003952118,0.0001433382,0.0001926087,0.9310097,0.006105395,0.02053061,0.0005898949,0.04094971],"study_design_scores_gemma":[0.00001494822,0.00006416927,0.00007479032,0.000004437669,0.000005226842,0.0000215306,0.00001439631,0.9943076,0.0005257772,0.003792807,0.001169801,0.000004495836],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01087841,0.0003095329,0.9855375,0.0001070053,0.00006094552,0.00003464553,0.00001064384,0.0001774189,0.00288396],"genre_scores_gemma":[0.9124367,0.0004255491,0.08159357,0.0000969699,0.00008363825,0.0002048621,0.00004226918,0.00003428993,0.005082117],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002461915,"threshold_uncertainty_score":0.004895151,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4287883046","doi":"10.1109/isie51582.2022.9831703","title":"Power Delivery Capability Improvement of Voltage Source Converters in Weak Power Grid Using Deep Reinforcement Learning with Continuous Action","year":2022,"lang":"en","type":"article","venue":"2022 IEEE 31st International Symposium on Industrial Electronics (ISIE)","topic":"Microgrid Control and Optimization","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Carleton University","funders":"","keywords":"Control theory (sociology); Phase-locked loop; Voltage source; Computer science; Controller (irrigation); Converters; AC power; Grid; Engineering; Voltage; Electronic engineering; Electrical engineering; Mathematics; Control (management)","authors":[{"name":"Osarodion E. Egbomwan","is_ca":true},{"name":"Hicham Chaoui","is_ca":true},{"name":"Shichao Liu","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.007839375407568355,"gpt":0.202015336703252,"spread":0.1941759612956836,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003902311,0.0004788881,0.0003107791,0.0001555528,0.0001369282,0.0003563672,0.0004181114,0.0002778966,0.0006695317],"category_scores_gemma":[0.0006133199,0.0001337726,0.000180719,0.0001250301,0.0002535885,0.0003040797,0.0003789716,0.000388896,0.00008531607],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002824161,"about_ca_system_score_gemma":0.0003512485,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003733116,"about_ca_topic_score_gemma":0.003395725,"domain_scores_codex":[0.9999194,0.00001910747,0.000005412553,0.00001501431,0.00002466169,0.00001643788],"domain_scores_gemma":[0.9997929,0.00008790669,0.00003762712,0.0000142117,0.00005331119,0.00001409333],"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":[0.00009963136,0.0001237469,0.0009536462,0.0000798246,0.00003386494,0.00008820967,0.00004420638,0.9165169,0.01000136,0.001307546,0.0004940754,0.07025684],"study_design_scores_gemma":[0.00000413262,0.00002950907,0.00008218842,0.000001464082,0.000002723125,0.000003308723,0.000001537121,0.9990982,0.0005598118,0.0001613564,0.00005484738,9.981208e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2952007,0.0005407046,0.6953748,0.0002867355,0.0000585131,0.00005957347,0.00002356314,0.0007295336,0.007725848],"genre_scores_gemma":[0.9909689,0.00005746987,0.008394009,0.00002192732,0.000004817936,0.00001148408,0.000009983423,0.000006647781,0.0005247685],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003733116,"threshold_uncertainty_score":0.007422805,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4287595676","doi":"10.1109/isie51582.2022.9831502","title":"Loss Comparison of Electric Vehicle Fuel Cell Integration Methods","year":2022,"lang":"en","type":"article","venue":"2022 IEEE 31st International Symposium on Industrial Electronics (ISIE)","topic":"Electric and Hybrid Vehicle Technologies","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Toronto","funders":"","keywords":"Drivetrain; Inverter; Dual (grammatical number); Automotive engineering; Harmonics; Driving cycle; Voltage source inverter; Voltage; Electric vehicle; Computer science; Power (physics); Engineering; Electrical engineering; Torque; Physics","authors":[{"name":"Yuheng Wang","is_ca":true},{"name":"Mehanathan Pathmanathan","is_ca":true},{"name":"Peter W. Lehn","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.02574692428326547,"gpt":0.2918162822024525,"spread":0.266069357919187,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009169945,0.0005117548,0.0005283054,0.001931545,0.0003261456,0.0009332165,0.001244067,0.0003543169,0.001994214],"category_scores_gemma":[0.002109708,0.0002778836,0.0003396829,0.001094409,0.0002674986,0.001292845,0.0005947463,0.0003354761,0.000627536],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008579056,"about_ca_system_score_gemma":0.0002703948,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001447412,"about_ca_topic_score_gemma":0.001742724,"domain_scores_codex":[0.9986839,0.00010288,0.00003805397,0.00009788389,0.0009791984,0.0000980587],"domain_scores_gemma":[0.9990747,0.0002335254,0.00006721101,0.00009230733,0.0005051235,0.00002713823],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.004005781,0.0007638801,0.02821305,0.001050869,0.0002803763,0.0003881514,0.0004792085,0.1075855,0.1161356,0.004865867,0.0034174,0.7328144],"study_design_scores_gemma":[0.0001859853,0.003796914,0.06231751,0.0001693315,0.0003475378,0.001168373,0.0007266051,0.4871542,0.4170557,0.001843821,0.02509793,0.0001360766],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.846981,0.00368644,0.1332742,0.0001433429,0.0001381822,0.0001462331,0.0003372885,0.0009254334,0.01436776],"genre_scores_gemma":[0.9736201,0.0008215698,0.01970572,0.00002658522,0.00001853904,0.00006885883,0.0004150781,0.0001127789,0.005210744],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001994214,"threshold_uncertainty_score":0.006671309,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4287848459","doi":"10.1109/isie51582.2022.9831643","title":"Monte Carlo Study of Jiles-Atherton Parameters on Hysteresis Area and Remnant Displacement","year":2022,"lang":"en","type":"article","venue":"2022 IEEE 31st International Symposium on Industrial Electronics (ISIE)","topic":"Piezoelectric Actuators and Control","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"York University","funders":"","keywords":"Monte Carlo method; Hysteresis; Displacement (psychology); Parameter space; Statistical physics; Physics; Mathematics; Statistics; Condensed matter physics","authors":[{"name":"Marc Savoie","is_ca":true},{"name":"Jinjun Shan","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.0172920988139794,"gpt":0.2181723443950831,"spread":0.2008802455811037,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001756538,0.0002213763,0.0004031311,0.0005954167,0.0004303712,0.0003212806,0.0004534618,0.0004740633,0.0008050872],"category_scores_gemma":[0.006977015,0.0002100683,0.0003059571,0.0004061996,0.0005625509,0.0005691937,0.0002117484,0.0004303035,0.00006152997],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004220526,"about_ca_system_score_gemma":0.0003848643,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002184761,"about_ca_topic_score_gemma":0.002721804,"domain_scores_codex":[0.9996719,0.0001210133,0.00001376226,0.00005209775,0.00008872629,0.00005247993],"domain_scores_gemma":[0.9922781,0.006492594,0.0003807573,0.0003990695,0.0003691256,0.00008023826],"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":[0.0002410074,0.0001078791,0.009638932,0.0001026891,0.00004975447,0.0001646441,0.0001670013,0.9516048,0.01140695,0.01661799,0.0004390827,0.009459148],"study_design_scores_gemma":[0.000007631186,0.00005118323,0.001500592,0.000007869387,0.00001042061,0.00003189702,0.0000277962,0.9933,0.003658175,0.001200337,0.0001938763,0.00001022317],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9613901,0.0003353229,0.03552169,0.0001127464,0.0000105146,0.00003228596,0.00005900591,0.00009370277,0.002444718],"genre_scores_gemma":[0.9931772,0.00005736354,0.006416942,0.00001314456,0.000002342126,0.00002734802,0.00004904196,0.00001734013,0.0002392521],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002184761,"threshold_uncertainty_score":0.009289563,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4287882643","doi":"10.1109/isie51582.2022.9831720","title":"Optimal Energy Saving Adaptive Cruise Control in Overtaking Scenarios for a Hybrid Electric Vehicle","year":2022,"lang":"en","type":"article","venue":"2022 IEEE 31st International Symposium on Industrial Electronics (ISIE)","topic":"Traffic control and management","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":"McMaster University","funders":"","keywords":"Overtaking; Cruise control; Cruise; Automotive engineering; Electric vehicle; Computer science; Energy consumption; Fuel efficiency; Jerk; Powertrain; Optimal control; Energy (signal processing); Hybrid vehicle; Control theory (sociology); Control (management); Engineering; Torque; Mathematical optimization; Acceleration; Power (physics); Aerospace engineering","authors":[{"name":"Pier Giuseppe Anselma","is_ca":true},{"name":"Waiyuntian Lou","is_ca":true},{"name":"Ali Emadi","is_ca":true},{"name":"Giovanni Belingardi","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.01209215106398879,"gpt":0.2112172046575964,"spread":0.1991250535936076,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002210001,0.0006116955,0.0003868931,0.0002185419,0.000240536,0.0005177591,0.0004079873,0.0004239001,0.0006923058],"category_scores_gemma":[0.0004318227,0.0002270897,0.000217265,0.0001713213,0.0002810482,0.0002584614,0.0003726721,0.000472544,0.00007892958],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003443914,"about_ca_system_score_gemma":0.0005901947,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01048019,"about_ca_topic_score_gemma":0.008576954,"domain_scores_codex":[0.9999057,0.00002044576,0.000003289183,0.00002194629,0.00001917508,0.00002935389],"domain_scores_gemma":[0.9998491,0.00007231524,0.0000283656,0.000006727764,0.00003071218,0.00001274605],"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":[0.00008165996,0.00002465417,0.0002686497,0.00002895764,0.00001093407,0.00004517495,0.00003575767,0.9819488,0.003537109,0.001121745,0.0001619302,0.01273461],"study_design_scores_gemma":[0.000006111036,0.00003703289,0.0001162828,0.000001444766,0.000002589017,0.000004161237,0.000008939025,0.9991172,0.0003440887,0.0002614405,0.0000990462,0.000001600223],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2115416,0.0003234884,0.7806023,0.0001838148,0.00003406291,0.00005861167,0.00004334785,0.0002742769,0.006938435],"genre_scores_gemma":[0.9900927,0.00004665995,0.008740507,0.00001534631,0.000005967782,0.0000190189,0.00001958493,0.00000903852,0.001051212],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01048019,"threshold_uncertainty_score":0.02083838,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4287882769","doi":"10.1109/isie51582.2022.9831475","title":"Rao-Blackwellized Variational Bayesian Smoother for Mobile Robot Localization","year":2022,"lang":"en","type":"article","venue":"2022 IEEE 31st International Symposium on Industrial Electronics (ISIE)","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"York University","funders":"","keywords":"Covariance; Noise (video); Estimator; Mobile robot; Landmark; Artificial intelligence; Bayesian probability; Computer science; Computer vision; Covariance matrix; Posterior probability; Estimation of covariance matrices; Noise measurement; Algorithm; Mathematics; Robot; Statistics; Noise reduction","authors":[{"name":"Shuo Zhang","is_ca":true},{"name":"Jinjun Shan","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.01361545640375982,"gpt":0.2311783162253643,"spread":0.2175628598216044,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001954082,0.0007278843,0.001302286,0.0007648425,0.0004623644,0.0009507893,0.00170917,0.001449612,0.00221974],"category_scores_gemma":[0.004967109,0.0007504459,0.001170458,0.0009961809,0.0009742466,0.001681154,0.001387566,0.00200308,0.0006900323],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001072079,"about_ca_system_score_gemma":0.002026809,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01114262,"about_ca_topic_score_gemma":0.007624669,"domain_scores_codex":[0.9989415,0.0003739935,0.00004640526,0.0001869036,0.0003626458,0.00008852653],"domain_scores_gemma":[0.9987628,0.000622216,0.0001128203,0.0001093079,0.0003344924,0.00005829054],"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":[0.0001376918,0.00003913534,0.000713742,0.0001527714,0.00009138206,0.00007213504,0.0001317847,0.8455557,0.005139349,0.07406572,0.002257802,0.07164282],"study_design_scores_gemma":[0.00000681249,0.000009914515,0.00007286239,0.000004322142,0.00000423075,0.000009105301,0.000004202496,0.9926642,0.0002588367,0.006203,0.000755143,0.000007432735],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001007517,0.00008606664,0.9985279,0.00004994122,0.00001513599,0.00000647343,0.00001658686,0.00009607226,0.0001943519],"genre_scores_gemma":[0.2821794,0.001032245,0.7081597,0.0002702226,0.0001838854,0.0002119823,0.0005683445,0.0003099773,0.007084224],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01114262,"threshold_uncertainty_score":0.02215552,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4287883007","doi":"10.1109/isie51582.2022.9831530","title":"A Hierarchical Pitman-Yor mixture of Scaled Dirichlet Distributions","year":2022,"lang":"en","type":"article","venue":"2022 IEEE 31st International Symposium on Industrial Electronics (ISIE)","topic":"Bayesian Methods and Mixture Models","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Concordia University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Mixture model; Robustness (evolution); Computer science; Dirichlet distribution; Inference; Cluster analysis; Latent Dirichlet allocation; Dirichlet process; Artificial intelligence; Flexibility (engineering); Hierarchical clustering; Hierarchical Dirichlet process; Gaussian; Machine learning; Data mining; Topic model; Mathematics; Statistics","authors":[{"name":"Ali Baghdadi","is_ca":true},{"name":"Narges Manouchehri","is_ca":true},{"name":"Nizar Bouguila","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.01924379398478389,"gpt":0.2698742535938535,"spread":0.2506304596090696,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003154163,0.001025645,0.001806879,0.001932506,0.001189769,0.001999962,0.004074562,0.002570699,0.00437897],"category_scores_gemma":[0.008544816,0.001148206,0.00249599,0.002030214,0.001757135,0.003237106,0.002296829,0.003061925,0.001948108],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00155705,"about_ca_system_score_gemma":0.001618468,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01053461,"about_ca_topic_score_gemma":0.01202082,"domain_scores_codex":[0.997893,0.000874058,0.00009014849,0.0005784368,0.0003775948,0.0001867812],"domain_scores_gemma":[0.9977945,0.001249684,0.0001674945,0.0002592088,0.0003921068,0.0001370213],"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":[0.0003428792,0.0001524295,0.0037877,0.0003336409,0.0002504327,0.0003551032,0.0008761314,0.5275683,0.007283632,0.31083,0.008968556,0.1392512],"study_design_scores_gemma":[0.00001791936,0.00002115451,0.0002430544,0.0000180665,0.00001912267,0.00006474498,0.00002948084,0.9599088,0.0005820683,0.03710455,0.001964004,0.0000270743],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.003709977,0.000219405,0.9948802,0.0001754709,0.00004392592,0.00004180602,0.00009464112,0.0002082026,0.0006263395],"genre_scores_gemma":[0.3060011,0.00106551,0.6779789,0.0006867904,0.0003019245,0.0006470673,0.001440586,0.0004854171,0.01139285],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01053461,"threshold_uncertainty_score":0.02094662,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null}]}