{"meta":{"query_hash":"e843e4b5b3be","filters":{"venue":"Information Geometry"},"cohort_total":6,"direct_labels_cover":0,"predictions_cover":6,"exported":6,"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/e843e4b5b3be","api":"https://metacan.xera.ac/api/v1/cohort?venue=Information+Geometry"},"results":[{"id":"W3194068170","doi":"10.1007/s41884-021-00053-7","title":"Pseudo-Riemannian geometry encodes information geometry in optimal transport","year":2021,"lang":"en","type":"article","venue":"Information Geometry","topic":"Geometric Analysis and Curvature Flows","field":"Mathematics","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada; University of Southern California; Connaught Fund; National Science Foundation","keywords":"Information geometry; Mathematics; Geodesic; Statistical manifold; Geometry; Riemannian geometry; Differential geometry; Constant curvature; Geometric flow; Curvature; Parallel transport; Divergence (linguistics); Convex geometry; Scalar curvature; Regular polygon","score_opus":0.014256324354916153,"score_gpt":0.25677351463443643,"score_spread":0.2425171902795203,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3194068170","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":[0.28205994,0.0009846556,0.68094265,0.0037947358,0.00023287421,0.00006242801,0.0005929377,0.0003178784,0.031011965],"genre_scores_gemma":[0.94421285,0.0005401237,0.045992374,0.00045304943,0.0002488858,0.00005870258,0.00033713382,0.0001774046,0.007979577],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9990177,0.00032128012,0.000057589274,0.00022397416,0.0002681072,0.00011124245],"domain_scores_gemma":[0.99696165,0.00084570283,0.00055237836,0.00034839413,0.0007862752,0.00050554035],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013336551,0.00060964626,0.0006592997,0.0022551173,0.00096329226,0.0025156671,0.00082469545,0.001265019,0.0031801807],"category_scores_gemma":[0.005003913,0.0003440229,0.0007578134,0.0008798326,0.0036720622,0.004949909,0.0023449757,0.0016445082,0.0005175223],"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":[0.000013343614,0.0000057468224,0.00026342503,0.000017039876,0.000005370248,0.0000700948,0.00007528786,0.0051528504,0.0007980168,0.9903514,0.00056783046,0.002679503],"study_design_scores_gemma":[0.0000044261606,0.000025797666,0.0005359191,0.000008693674,0.00000413216,0.00010055236,0.000051358493,0.06042474,0.0003943279,0.9364373,0.0019974685,0.000015356909],"about_ca_topic_score_codex":0.0019851557,"about_ca_topic_score_gemma":0.0011923113,"teacher_disagreement_score":0.0031801807,"about_ca_system_score_codex":0.0021748182,"about_ca_system_score_gemma":0.0007559043,"threshold_uncertainty_score":0.015779555},"labels":[],"label_agreement":null},{"id":"W4226052975","doi":"10.1007/s41884-022-00070-0","title":"Laplacian operator on statistical manifold","year":2022,"lang":"en","type":"article","venue":"Information Geometry","topic":"Geometric Analysis and Curvature Flows","field":"Mathematics","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia, Okanagan Campus; Kelowna General Hospital; University of British Columbia; Carleton University","funders":"","keywords":"Laplace operator; Vector Laplacian; Mathematics; Manifold (fluid mechanics); Manifold alignment; Operator (biology); Statistical manifold; Pure mathematics; Laplacian matrix; Kernel (algebra); Heat kernel; Computer science; Mathematical analysis; Artificial intelligence; Nonlinear dimensionality reduction; Physics; Vector potential; Information geometry; Chemistry; Geometry","score_opus":0.01980564271858374,"score_gpt":0.27252523974286563,"score_spread":0.2527195970242819,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4226052975","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":[0.24607614,0.0071806787,0.6582579,0.014759617,0.00080701016,0.0000655779,0.00081439485,0.0005079922,0.071530744],"genre_scores_gemma":[0.91855925,0.0039680935,0.043241344,0.0011974747,0.0018418055,0.000100943646,0.00044022643,0.00019395944,0.030456917],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9993297,0.00026996515,0.000028384247,0.00014907315,0.00016512541,0.000057829086],"domain_scores_gemma":[0.9974324,0.001186066,0.00029387683,0.00022896582,0.0005530475,0.00030562817],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014373556,0.0008179009,0.00095817953,0.003987147,0.0011580564,0.0028943948,0.00088015286,0.0015093905,0.005061218],"category_scores_gemma":[0.004269217,0.00037165196,0.0006319372,0.0020588709,0.0033064163,0.005280643,0.0016757908,0.0020218675,0.00046226877],"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":[0.00000395752,0.000005416366,0.00009128593,0.000012471283,0.000004679792,0.00002412874,0.000087102,0.0008584935,0.00030142398,0.99629897,0.00060408155,0.0017079216],"study_design_scores_gemma":[0.0000023069417,0.0000072533126,0.00020665336,0.00000481539,0.0000034668938,0.00004678406,0.000025589383,0.010993107,0.00009112606,0.9869866,0.0016240802,0.000008204944],"about_ca_topic_score_codex":0.0016114601,"about_ca_topic_score_gemma":0.0010955636,"teacher_disagreement_score":0.005061218,"about_ca_system_score_codex":0.0016878825,"about_ca_system_score_gemma":0.0008255623,"threshold_uncertainty_score":0.016931415},"labels":[],"label_agreement":null},{"id":"W4311401913","doi":"10.1007/s41884-022-00089-3","title":"Conformal mirror descent with logarithmic divergences","year":2022,"lang":"en","type":"article","venue":"Information Geometry","topic":"Markov Chains and Monte Carlo Methods","field":"Mathematics","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Vector Institute; University of Toronto","funders":"Connaught Fund; Natural Sciences and Engineering Research Council of Canada; Canadian Institute for Advanced Research","keywords":"Conformal map; Mathematics; Logarithm; Bregman divergence; Gradient descent; Stochastic gradient descent; Duality (order theory); Hessian matrix; Divergence (linguistics); Descent (aeronautics); Generalization; Applied mathematics; Regular polygon; Simplex; Mathematical analysis; Pure mathematics; Combinatorics; Geometry; Computer science; Physics; Artificial neural network","score_opus":0.038631270062971304,"score_gpt":0.29362628209178676,"score_spread":0.25499501202881547,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4311401913","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":[0.10917587,0.00043272192,0.8753746,0.0012293846,0.00014713546,0.000063276566,0.00016162042,0.00022849701,0.0131869],"genre_scores_gemma":[0.90328616,0.00052062725,0.079732925,0.00046894967,0.00020113915,0.00013178957,0.0001923582,0.00023158304,0.015234509],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99926656,0.00026090464,0.000032504977,0.00016222495,0.00017849203,0.00009936463],"domain_scores_gemma":[0.99788445,0.00092011195,0.00026002424,0.00028820924,0.00036218797,0.0002848882],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016557241,0.0006039174,0.0008138166,0.00081692525,0.0008746893,0.0016476457,0.0010106749,0.0013492685,0.004248476],"category_scores_gemma":[0.0094353715,0.0004001212,0.00089780113,0.0005200937,0.0024797476,0.0033365819,0.0021616553,0.0019584424,0.00048033224],"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":[0.000032878634,0.000022582484,0.00076015876,0.000031485775,0.00001487694,0.000121449666,0.00008764058,0.03458311,0.0015043401,0.9550112,0.00092920073,0.0069011417],"study_design_scores_gemma":[0.000014670473,0.000034622848,0.0004236521,0.00001508436,0.000005204382,0.00009475688,0.000032992044,0.40699995,0.00069649366,0.59001654,0.0016461803,0.000019893476],"about_ca_topic_score_codex":0.002835923,"about_ca_topic_score_gemma":0.0018714623,"teacher_disagreement_score":0.004248476,"about_ca_system_score_codex":0.0018163319,"about_ca_system_score_gemma":0.0010898147,"threshold_uncertainty_score":0.014212549},"labels":[],"label_agreement":null},{"id":"W4391474148","doi":"10.1007/s41884-023-00129-6","title":"Variational representations of annealing paths: Bregman information under monotonic embedding","year":2024,"lang":"en","type":"article","venue":"Information Geometry","topic":"Statistical Mechanics and Entropy","field":"Physics and Astronomy","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Vector Institute","funders":"","keywords":"Monotonic function; Embedding; Simulated annealing; Bregman divergence; Mathematics; Mathematical optimization; Computer science; Applied mathematics; Pure mathematics; Artificial intelligence; Mathematical analysis","score_opus":0.008637735874800252,"score_gpt":0.27895420617146244,"score_spread":0.27031647029666217,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4391474148","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":[0.08047904,0.000849667,0.90397745,0.0020563002,0.00008806079,0.000049508457,0.0003446,0.00020999949,0.011945298],"genre_scores_gemma":[0.80744743,0.0016928534,0.17100517,0.0007058471,0.0003194434,0.00026546296,0.00075562444,0.0006088033,0.017199285],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9987956,0.0005759171,0.000048246933,0.00024353979,0.00019990001,0.0001367396],"domain_scores_gemma":[0.99324656,0.004232114,0.0005914212,0.00082597765,0.0006209433,0.0004830355],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0038578091,0.00088921667,0.0013715618,0.0018231153,0.0011532843,0.0033872568,0.0028960952,0.0035616101,0.0061011147],"category_scores_gemma":[0.015580027,0.0011344817,0.0011615641,0.0017258222,0.0036079956,0.009786805,0.0029111125,0.004491492,0.00063598],"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":[0.000019732644,0.000014262491,0.00008690324,0.000022308683,0.0000069520634,0.000012115079,0.000081220875,0.026652033,0.00019810244,0.9690785,0.00053882576,0.0032891412],"study_design_scores_gemma":[0.0000040302953,0.000009686135,0.00006866851,0.000010067588,0.0000028817124,0.000009659751,0.00001623718,0.16195172,0.00008310031,0.8374507,0.00038308566,0.000010182629],"about_ca_topic_score_codex":0.0031093585,"about_ca_topic_score_gemma":0.0024289282,"teacher_disagreement_score":0.0061011147,"about_ca_system_score_codex":0.0023938925,"about_ca_system_score_gemma":0.001851543,"threshold_uncertainty_score":0.02041024},"labels":[],"label_agreement":null},{"id":"W4392162285","doi":"10.1007/s41884-024-00132-5","title":"Publisher Correction: Variational representations of annealing paths: Bregman information under monotonic embedding","year":2024,"lang":"en","type":"article","venue":"Information Geometry","topic":"Statistical Mechanics and Entropy","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Vector Institute","funders":"","keywords":"Monotonic function; Embedding; Simulated annealing; Mathematics; Annealing (glass); Applied mathematics; Computer science; Mathematical optimization; Artificial intelligence; Mathematical analysis; Physics; Thermodynamics","score_opus":0.008318162061812647,"score_gpt":0.2686544168136576,"score_spread":0.26033625475184496,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4392162285","genre_codex":"editorial","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00130933,0.0028809395,0.029513447,0.07739611,0.8533355,0.00005437165,0.0052036643,0.0019624187,0.028344277],"genre_scores_gemma":[0.12486466,0.0089560915,0.047042817,0.030527022,0.19444604,0.00035775322,0.007157449,0.0066651744,0.579983],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9961138,0.00080729806,0.0004478702,0.00072976266,0.0016686657,0.00023257213],"domain_scores_gemma":[0.9734838,0.0065921764,0.0009279284,0.0037418096,0.014632979,0.0006213621],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0036942374,0.0016887449,0.0017888416,0.0037403477,0.0024962125,0.005183132,0.0046308474,0.005832562,0.09320081],"category_scores_gemma":[0.07706148,0.0011727683,0.0013130603,0.0055761375,0.0028179795,0.005824459,0.0018482244,0.008620575,0.027863082],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000041605308,0.0000066253206,0.00009316761,0.00015933755,0.000029074283,0.000106340995,0.00006355763,0.0008306837,0.000066588196,0.06008953,0.9251085,0.013405059],"study_design_scores_gemma":[0.00006790962,0.00003201787,0.0009547309,0.00032486615,0.00010518719,0.0006523646,0.00011085766,0.009326431,0.0011291683,0.14486961,0.8423038,0.00012312063],"about_ca_topic_score_codex":0.012088974,"about_ca_topic_score_gemma":0.014164368,"teacher_disagreement_score":0.09320081,"about_ca_system_score_codex":0.0039949943,"about_ca_system_score_gemma":0.004413871,"threshold_uncertainty_score":0.31178772},"labels":[],"label_agreement":null},{"id":"W4401921664","doi":"10.1007/s41884-024-00145-0","title":"Unveiling cellular morphology: statistical analysis using a Riemannian elastic metric in cancer cell image datasets","year":2024,"lang":"en","type":"article","venue":"Information Geometry","topic":"Cell Image Analysis Techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Division of Civil, Mechanical and Manufacturing Innovation; National Science Foundation","keywords":"Metric (unit); Morphology (biology); Image (mathematics); Statistical analysis; Computer science; Mathematics; Artificial intelligence; Geology; Statistics; Engineering","score_opus":0.007665103440556722,"score_gpt":0.2971198079015533,"score_spread":0.2894547044609966,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4401921664","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":[0.57764614,0.00093252683,0.41093802,0.0009853293,0.00006315761,0.00010629015,0.006257967,0.002284797,0.00078573753],"genre_scores_gemma":[0.8675438,0.00032739257,0.12141441,0.00011598924,0.000047890302,0.00015039726,0.009355971,0.0003995939,0.0006445817],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988741,0.00036137697,0.0001030961,0.00025992468,0.00030025904,0.0001010951],"domain_scores_gemma":[0.99576026,0.0020710675,0.00052103284,0.00088196195,0.00061089155,0.00015486569],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0034243295,0.00075306284,0.0008574733,0.0025841037,0.00053236476,0.0014596011,0.0008765574,0.0010743113,0.0005229872],"category_scores_gemma":[0.010382904,0.00029639536,0.0010767048,0.0025868262,0.0008470502,0.0010470957,0.0012992442,0.001100439,0.00029645412],"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":[0.001203548,0.0004917114,0.10023401,0.0009720189,0.001162406,0.00056951924,0.0007228121,0.36669344,0.13745016,0.021667222,0.016705828,0.3521274],"study_design_scores_gemma":[0.000016611648,0.00012145293,0.035301067,0.000024843914,0.0000942703,0.0003000599,0.00015949729,0.92867756,0.02088783,0.01079612,0.0035539293,0.00006681081],"about_ca_topic_score_codex":0.0041234065,"about_ca_topic_score_gemma":0.00782385,"teacher_disagreement_score":0.0041234065,"about_ca_system_score_codex":0.0007430468,"about_ca_system_score_gemma":0.0010107033,"threshold_uncertainty_score":0.018109798},"labels":[],"label_agreement":null}]}