{"meta":{"query_hash":"ba19c855b3c4","filters":{"venue":"AMW"},"cohort_total":5,"direct_labels_cover":0,"predictions_cover":5,"exported":5,"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/ba19c855b3c4","api":"https://metacan.xera.ac/api/v1/cohort?venue=AMW"},"results":[{"id":"W2398876418","doi":"","title":"On Conditional Chase Termination.","year":2011,"lang":"en","type":"article","venue":"AMW","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Computer science; Chase","score_opus":0.030194407157634627,"score_gpt":0.2364884310248795,"score_spread":0.20629402386724485,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2398876418","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":[0.023032863,0.0027643705,0.8529133,0.0072200308,0.0017729864,0.00029806865,0.00094238017,0.0050058193,0.10605013],"genre_scores_gemma":[0.60341674,0.0035389825,0.26080146,0.0080005005,0.0035696232,0.0014511065,0.004229369,0.0050852676,0.109906875],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99212974,0.002460778,0.0005432827,0.0010795712,0.0024673871,0.0013191494],"domain_scores_gemma":[0.9669893,0.021425487,0.0008394711,0.0061655724,0.0036941173,0.0008861578],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008843668,0.0013003343,0.0018656942,0.002377816,0.0034441166,0.004397799,0.003202281,0.0028546727,0.018651152],"category_scores_gemma":[0.038544077,0.0012086476,0.001785145,0.002409047,0.0064355256,0.017717004,0.010176212,0.0083951,0.0051742876],"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":[0.00033728892,0.000080007165,0.0008467354,0.00017128578,0.00004909779,0.00023882287,0.0005431516,0.0032137656,0.0011375715,0.9320893,0.024114236,0.03717882],"study_design_scores_gemma":[0.00006151879,0.000029174882,0.00016482387,0.000053855532,0.000046655707,0.00013250324,0.00007697282,0.015851947,0.0010020635,0.96963376,0.012924775,0.000022101043],"about_ca_topic_score_codex":0.0031685745,"about_ca_topic_score_gemma":0.0038664057,"teacher_disagreement_score":0.018651152,"about_ca_system_score_codex":0.0025192676,"about_ca_system_score_gemma":0.002484208,"threshold_uncertainty_score":0.06239432},"labels":[],"label_agreement":null},{"id":"W2402585642","doi":"","title":"GDE: General Data Exchange with Schema and Data Level Mappings.","year":2013,"lang":"en","type":"article","venue":"AMW","topic":"Semantic Web and Ontologies","field":"Computer Science","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":"University of Ottawa","funders":"","keywords":"Computer science; Schema (genetic algorithms); Data exchange; Set (abstract data type); Theoretical computer science; Information retrieval; Knowledge base; Data mining; Database; Artificial intelligence; Programming language","score_opus":0.1849158307224279,"score_gpt":0.3045156726178656,"score_spread":0.11959984189543771,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2402585642","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":[0.0015258472,0.001159651,0.9837595,0.0021777523,0.00030525198,0.0005301513,0.0016225978,0.0018099324,0.0071093286],"genre_scores_gemma":[0.054948412,0.002255959,0.9220268,0.0027732472,0.0006452499,0.0018754881,0.0074321837,0.0006870173,0.007355757],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.97388905,0.010819466,0.004069068,0.005309029,0.0048807445,0.0010326965],"domain_scores_gemma":[0.97928226,0.006421024,0.0012828754,0.010964083,0.0013613597,0.0006883863],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.017061519,0.0019162466,0.0021724706,0.0039265445,0.0024593147,0.010876314,0.007301461,0.005913572,0.008540842],"category_scores_gemma":[0.031706817,0.0020978325,0.0032520383,0.008348942,0.0066392254,0.025837164,0.01521817,0.008980114,0.0058099832],"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":[0.00011449771,0.00007513442,0.00056106725,0.0004306252,0.000075394535,0.00041856087,0.0007184324,0.0038349628,0.001122022,0.9306825,0.015888788,0.04607806],"study_design_scores_gemma":[0.00006995036,0.00007610134,0.00027455686,0.00032983196,0.00005965475,0.0013275304,0.00034159102,0.028363748,0.0022898098,0.6862228,0.28057873,0.00006564827],"about_ca_topic_score_codex":0.0030921956,"about_ca_topic_score_gemma":0.0018339726,"teacher_disagreement_score":0.017061519,"about_ca_system_score_codex":0.003939082,"about_ca_system_score_gemma":0.0040236684,"threshold_uncertainty_score":0.090231},"labels":[],"label_agreement":null},{"id":"W2403315168","doi":"","title":"On Axiomatization and Inference Complexity over a Hierarchy of Functional Dependencies.","year":2015,"lang":"en","type":"article","venue":"AMW","topic":"Data Quality and Management","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo; Ontario Tech University","funders":"","keywords":"Functional dependency; Inference; Hierarchy; Tuple; Mathematics; Dependency theory (database theory); Rule of inference; Theoretical computer science; Metric (unit); Antecedent (behavioral psychology); Focus (optics); Extension (predicate logic); Computer science; Algorithm; Discrete mathematics; Data mining; Artificial intelligence; Relational database; Programming language","score_opus":0.5096816871169793,"score_gpt":0.44880443507436196,"score_spread":0.06087725204261729,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2403315168","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":[0.019370334,0.0005778258,0.9720257,0.0022039963,0.0000635385,0.00033272547,0.0011024429,0.0009307816,0.0033927136],"genre_scores_gemma":[0.14058365,0.00073878,0.85285085,0.00090140646,0.00028278527,0.00042095242,0.0023630175,0.00025866248,0.0015998419],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9760199,0.008423318,0.0023589062,0.00517834,0.0066935415,0.0013259957],"domain_scores_gemma":[0.78430474,0.19135994,0.0044214604,0.0118498765,0.0070706434,0.0009933922],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.016694846,0.001498187,0.0019201045,0.003977607,0.002315319,0.006038649,0.0050596,0.002394569,0.008455924],"category_scores_gemma":[0.09814243,0.0019117065,0.0063650482,0.0061788545,0.005252669,0.019295648,0.006149217,0.009843538,0.0010162097],"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":[0.00033979325,0.0005313651,0.0069832043,0.0017126604,0.00051460456,0.0007232601,0.0013088913,0.16999817,0.0049066925,0.5522287,0.0111027295,0.24964991],"study_design_scores_gemma":[0.00007659594,0.000057782872,0.0011125355,0.00010012933,0.00015154821,0.00035313793,0.0001470138,0.36499363,0.002519026,0.6261682,0.0042558014,0.00006464423],"about_ca_topic_score_codex":0.013797811,"about_ca_topic_score_gemma":0.018113913,"teacher_disagreement_score":0.016694846,"about_ca_system_score_codex":0.0066594803,"about_ca_system_score_gemma":0.005913902,"threshold_uncertainty_score":0.088291824},"labels":[],"label_agreement":null},{"id":"W2579485143","doi":"","title":"Query Planning for Evaluating SPARQL Property Paths.","year":2016,"lang":"en","type":"article","venue":"AMW","topic":"Semantic Web and Ontologies","field":"Computer Science","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":"York University","funders":"","keywords":"SPARQL; Computer science; Query optimization; RDF; Query plan; Property (philosophy); RDF query language; Query language; Plan (archaeology); Graph; Information retrieval; Sargable; Web query classification; Theoretical computer science; Database; Search engine; Web search query; Semantic Web","score_opus":0.11692841413509311,"score_gpt":0.34494227294052426,"score_spread":0.22801385880543115,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2579485143","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":[0.0029074242,0.00018217888,0.98545825,0.00031299223,0.000041371175,0.00028011366,0.00096810685,0.005970266,0.003879236],"genre_scores_gemma":[0.076168515,0.00028123983,0.9160595,0.00022813276,0.00004349964,0.0004461199,0.0031370681,0.0016096365,0.002026172],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99389815,0.0021773882,0.00048817953,0.0006308855,0.0025166094,0.00028882994],"domain_scores_gemma":[0.99351573,0.0036322353,0.00036377524,0.0013398678,0.0010256233,0.00012276214],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00503207,0.0012030362,0.00070662104,0.0014429394,0.00084340386,0.0024083846,0.0017692157,0.00093474303,0.009040514],"category_scores_gemma":[0.015778791,0.00080409704,0.0018280369,0.0019511833,0.0013299977,0.004437387,0.0026074366,0.001995681,0.0019239107],"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":[0.00046686083,0.00026751103,0.0034833995,0.0012875048,0.00027463792,0.00041412775,0.0008251314,0.1670753,0.012886531,0.30489507,0.05119774,0.45692617],"study_design_scores_gemma":[0.00007224536,0.00008211008,0.0005364513,0.00011530758,0.00007470926,0.00024563482,0.0003124627,0.7279319,0.01367592,0.20795433,0.04894574,0.000053195206],"about_ca_topic_score_codex":0.007915443,"about_ca_topic_score_gemma":0.013035102,"teacher_disagreement_score":0.009040514,"about_ca_system_score_codex":0.0017394397,"about_ca_system_score_gemma":0.0022801473,"threshold_uncertainty_score":0.030243516},"labels":[],"label_agreement":null},{"id":"W56576261","doi":"","title":"Information Integration: a Vision for Integration Independence and Linking Open Data.","year":2010,"lang":"en","type":"article","venue":"AMW","topic":"Advanced Database Systems and Queries","field":"Computer Science","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":"University of Toronto","funders":"","keywords":"Independence (probability theory); Data integration; Information integration; Computer science; Data mining; Mathematics","score_opus":0.02859230865770166,"score_gpt":0.3279443309987999,"score_spread":0.2993520223410982,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W56576261","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":[0.0031958898,0.0043397285,0.96833426,0.006921926,0.0005762235,0.00015240339,0.00072996377,0.0029732147,0.012776302],"genre_scores_gemma":[0.07426142,0.0058357106,0.9020404,0.0031497558,0.0015994094,0.00041839477,0.0040048794,0.000876766,0.007813204],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.98125595,0.005705584,0.00197581,0.0030946801,0.007162922,0.00080499076],"domain_scores_gemma":[0.97051245,0.008166273,0.0017033451,0.013632656,0.004365088,0.0016201156],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.021827081,0.0011812476,0.0020188678,0.008940527,0.002575585,0.017975854,0.006198301,0.0037628603,0.0045114756],"category_scores_gemma":[0.039234288,0.0015265071,0.0024809155,0.011241752,0.007448595,0.041302737,0.01496391,0.006801332,0.0042290585],"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":[0.00012849753,0.0001361407,0.0013797944,0.0005926476,0.00022108843,0.00017237244,0.0015264342,0.0016849029,0.0027551528,0.73986673,0.031650767,0.21988548],"study_design_scores_gemma":[0.000030650135,0.00004777023,0.00047395565,0.0003426835,0.00013596486,0.00025396177,0.00048641206,0.009758129,0.0030166619,0.81833696,0.16705391,0.000062860665],"about_ca_topic_score_codex":0.0027642946,"about_ca_topic_score_gemma":0.0014562295,"teacher_disagreement_score":0.021827081,"about_ca_system_score_codex":0.0017869694,"about_ca_system_score_gemma":0.005455672,"threshold_uncertainty_score":0.11543405},"labels":[],"label_agreement":null}]}