{"meta":{"query_hash":"5974456c80d4","filters":{"venue":"Semantic web and beyond"},"cohort_total":7,"direct_labels_cover":0,"predictions_cover":7,"exported":7,"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/5974456c80d4","api":"https://metacan.xera.ac/api/v1/cohort?venue=Semantic+web+and+beyond"},"results":[{"id":"W108438889","doi":"10.1007/978-0-387-34347-1_4","title":"A Trust Model for Sharing Ratings of Information Providers on the Semantic Web","year":2006,"lang":"en","type":"book-chapter","venue":"Semantic web and beyond","topic":"Access Control and Trust","field":"Social Sciences","cited_by":3,"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 Waterloo","funders":"","keywords":"Context (archaeology); Reliability (semiconductor); Internet privacy; Value (mathematics); Trustworthiness; Computer science; World Wide Web","score_opus":0.01827176391505384,"score_gpt":0.24787282480561104,"score_spread":0.2296010608905572,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W108438889","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.008335002,0.00019908504,0.0007470863,0.004001941,0.00019353784,0.0016391634,0.00010874851,0.000061258645,0.98471415],"genre_scores_gemma":[0.8698931,0.00011045366,0.00008471093,0.00049010996,0.00019810963,0.000037868405,0.00003289294,0.000021753447,0.129131],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99866945,0.000013668679,0.0004271547,0.00022227885,0.00039904926,0.00026837652],"domain_scores_gemma":[0.9989827,0.00020451052,0.0004188758,0.00019931285,0.00013940461,0.000055169952],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00046680486,0.00022985344,0.00035201374,0.00013815371,0.0005244837,0.00022541182,0.00028543785,0.00024091764,0.000040166924],"category_scores_gemma":[0.00010025318,0.00016314333,0.00014903746,0.00004391792,0.00029014784,0.00042185493,0.000063796506,0.0002012557,0.000012250128],"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":[0.000048899736,0.000017101192,0.00012340792,0.00032457995,0.00007177339,9.889479e-7,0.0032416084,0.00013916596,0.00003900242,0.9850235,0.006499649,0.004470318],"study_design_scores_gemma":[0.0024113704,0.00024192999,0.00014468608,0.00097288983,0.0006925057,0.0000028378108,0.0024976092,0.43573165,0.00003270673,0.44681373,0.109362595,0.0010954753],"about_ca_topic_score_codex":0.00030655166,"about_ca_topic_score_gemma":0.0009057611,"teacher_disagreement_score":0.8615581,"about_ca_system_score_codex":0.00003264983,"about_ca_system_score_gemma":0.00025147595,"threshold_uncertainty_score":0.6652792},"labels":[],"label_agreement":null},{"id":"W1483126190","doi":"10.1007/978-0-387-34347-1_5","title":"A Distributed Agent System upon Semantic Web Technologies to Provide Biological Data","year":2006,"lang":"en","type":"book-chapter","venue":"Semantic web and beyond","topic":"Bioinformatics and Genomic Networks","field":"Biochemistry, Genetics and Molecular Biology","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":"Concordia University","funders":"","keywords":"Biological data; Computer science; Biological database; Ontology; Semantic Web; World Wide Web; Data science; Bioinformatics; Biology","score_opus":0.016347741152233496,"score_gpt":0.22336195602731246,"score_spread":0.20701421487507896,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1483126190","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.18730952,0.07460692,0.04038412,0.012260705,0.006143948,0.015804421,0.035733134,0.0026403107,0.62511694],"genre_scores_gemma":[0.956866,0.0018036187,0.0010210703,0.00027663042,0.0005726882,0.000036290134,0.009506925,0.000090838104,0.029825905],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9977237,0.000020351305,0.00063474884,0.0009129518,0.00020238328,0.0005058655],"domain_scores_gemma":[0.9980833,0.00002242965,0.00027630496,0.0014121827,0.00007582982,0.0001299298],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002652122,0.00056936854,0.000617839,0.00012072849,0.00016030253,0.000117124415,0.000780577,0.0010202728,0.000010928747],"category_scores_gemma":[0.000035628243,0.00045224745,0.00012807602,0.000055551365,0.00018606949,0.0000067738006,0.0016198729,0.00033153826,0.00007092368],"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":[0.0006026656,0.00030368153,0.00051497394,0.004279988,0.002069203,0.00053460343,0.00008477097,0.00019937298,0.08838966,0.056001395,0.76275104,0.084268615],"study_design_scores_gemma":[0.00071943627,0.00055396045,0.000040061164,0.0004977315,0.0002678303,0.00021126732,0.0001665653,0.0054803025,0.0006649572,0.0016210276,0.98862016,0.0011566753],"about_ca_topic_score_codex":0.000011703735,"about_ca_topic_score_gemma":0.00012493265,"teacher_disagreement_score":0.7695565,"about_ca_system_score_codex":0.00003774159,"about_ca_system_score_gemma":0.00013738431,"threshold_uncertainty_score":0.99979293},"labels":[],"label_agreement":null},{"id":"W1503354104","doi":"10.1007/978-0-387-34347-1_14","title":"Completion Rules for Uncertainty Reasoning with the Description Logic ALC","year":2006,"lang":"en","type":"book-chapter","venue":"Semantic web and beyond","topic":"Semantic Web and Ontologies","field":"Computer Science","cited_by":8,"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":"Description logic; Computer science; Web Ontology Language; Ontology; Expressive power; Semantic Web; Knowledge base; Popularity; Theoretical computer science; Ontology language; Foundation (evidence); Artificial intelligence","score_opus":0.02314672149685751,"score_gpt":0.22611379211800528,"score_spread":0.20296707062114777,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1503354104","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.007882991,0.0059077856,0.57859445,0.011149548,0.001084102,0.0021440054,0.00006967167,0.00064459245,0.39252287],"genre_scores_gemma":[0.5705308,0.0009826373,0.08379532,0.00397855,0.0015161465,0.00017485998,0.00046431096,0.00017726661,0.33838013],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9984962,0.000027546286,0.00025801006,0.00057709863,0.00030530072,0.0003358691],"domain_scores_gemma":[0.9988172,0.00023400415,0.00025046253,0.0005055624,0.00014296293,0.0000498034],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002910363,0.0003614917,0.00042384764,0.000110957386,0.00040302865,0.00033077112,0.00050343294,0.0002097997,0.000008699549],"category_scores_gemma":[0.000018059045,0.00021514157,0.00011428399,0.00004288252,0.0002719366,0.00018038075,0.00014922634,0.00021356663,0.000014885245],"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":[0.000029106572,0.000016186183,0.000072285315,0.000115480914,0.00006825366,0.00002085929,0.00014572432,0.0000663663,0.00012429754,0.97575825,0.01649434,0.007088851],"study_design_scores_gemma":[0.0021843584,0.001055595,0.005105165,0.0009936264,0.00059761875,0.0004488256,0.0003276891,0.06663365,0.00008016883,0.5505644,0.37012067,0.0018882195],"about_ca_topic_score_codex":0.00007123911,"about_ca_topic_score_gemma":0.00034357145,"teacher_disagreement_score":0.5626478,"about_ca_system_score_codex":0.000039027345,"about_ca_system_score_gemma":0.000081576494,"threshold_uncertainty_score":0.87732184},"labels":[],"label_agreement":null},{"id":"W1510421640","doi":"10.1007/978-0-387-34347-1_11","title":"Ontoligent Interactive Query Tool","year":2006,"lang":"en","type":"book-chapter","venue":"Semantic web and beyond","topic":"Biomedical Text Mining and Ontologies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":15,"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; Query language; Web query classification; RDF query language; Information retrieval; Query optimization; Sargable; Web search query; Query expansion; Variety (cybernetics); Syntax; Ontology; Semantic reasoner; Download; World Wide Web; Search engine; Natural language processing; Artificial intelligence","score_opus":0.008920276348439282,"score_gpt":0.23620889445504387,"score_spread":0.22728861810660458,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1510421640","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.029190395,0.010961004,0.0004568936,0.00065627345,0.0008815893,0.00032759426,0.00019625814,0.00006578193,0.9572642],"genre_scores_gemma":[0.17101815,0.0017064135,0.00066176895,0.0007750574,0.0010223539,0.000012322434,0.0005836792,0.00006901924,0.8241512],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9988736,0.000014012093,0.00025572983,0.00047507524,0.00015009439,0.00023151809],"domain_scores_gemma":[0.99943775,0.000024681523,0.00012473566,0.00029120335,0.00005050406,0.00007112577],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000078027086,0.00030430077,0.00031906395,0.00006324298,0.0000680612,0.00003339444,0.00013418954,0.0005596868,0.00008520656],"category_scores_gemma":[0.00003138407,0.0002558849,0.00013572806,0.000011315138,0.00025414358,0.0000017419122,0.00016615324,0.00022891596,0.00004055495],"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":[0.00040763093,0.0002355516,0.00048438023,0.0005656255,0.0012778438,0.00035627472,0.0002761424,0.0000031126795,0.08141982,0.015964951,0.577739,0.32126966],"study_design_scores_gemma":[0.00035734643,0.00030978085,0.00017760403,0.0001239261,0.000097686454,0.000067185116,0.000041658117,0.000018745359,0.0018502468,0.002919177,0.99358255,0.00045411813],"about_ca_topic_score_codex":0.00002189896,"about_ca_topic_score_gemma":0.000109244764,"teacher_disagreement_score":0.41584352,"about_ca_system_score_codex":0.00001402413,"about_ca_system_score_gemma":0.000094214585,"threshold_uncertainty_score":0.99998933},"labels":[],"label_agreement":null},{"id":"W1511467690","doi":"10.1007/978-0-387-34347-1_13","title":"Resolution Based Explanations for Reasoning in the Description Logic ALC","year":2006,"lang":"en","type":"book-chapter","venue":"Semantic web and beyond","topic":"Semantic Web and Ontologies","field":"Computer Science","cited_by":4,"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":"Description logic; Construct (python library); Resolution (logic); Computer science; Automated reasoning; Non-monotonic logic; Artificial intelligence; Theoretical computer science; Natural language processing; Programming language","score_opus":0.03325301858308187,"score_gpt":0.24494817631865862,"score_spread":0.21169515773557673,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1511467690","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.001026263,0.003908566,0.6284728,0.009821219,0.0009777838,0.0015691011,0.000046898345,0.00026870324,0.3539087],"genre_scores_gemma":[0.76793134,0.0006237356,0.11496455,0.005296746,0.00090451905,0.00028153748,0.0005084141,0.00009624595,0.109392926],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99867564,0.000042139658,0.00030781122,0.0004459637,0.00025660585,0.0002718614],"domain_scores_gemma":[0.99898934,0.00032428862,0.00016033721,0.00042916767,0.00006870699,0.000028151922],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00048626214,0.00023687717,0.00026763818,0.0002570458,0.00022033179,0.0002171756,0.0004651484,0.00022880892,0.00000617357],"category_scores_gemma":[0.000060507267,0.00017298944,0.00010009256,0.000078008736,0.00009141424,0.0001990058,0.00006515638,0.0001978484,0.000009073933],"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":[0.000010040672,0.000030546085,0.00009055596,0.00008041893,0.0000128303855,0.000030044686,0.00019674693,0.00008337679,0.00008289282,0.98185813,0.013447261,0.004077174],"study_design_scores_gemma":[0.0020867102,0.0004418929,0.006248033,0.0007434886,0.00020831042,0.00012695204,0.00027194273,0.27592263,0.000058675712,0.5328272,0.17987111,0.0011930456],"about_ca_topic_score_codex":0.00005412238,"about_ca_topic_score_gemma":0.0004924124,"teacher_disagreement_score":0.76690507,"about_ca_system_score_codex":0.00004202152,"about_ca_system_score_gemma":0.000092840535,"threshold_uncertainty_score":0.7054305},"labels":[],"label_agreement":null},{"id":"W2123328799","doi":"10.1007/978-0-387-34347-1_9","title":"Toward the Identification and Elimination of Semantic Conflicts for the Integration of RuleML-based Ontologies","year":2006,"lang":"en","type":"book-chapter","venue":"Semantic web and beyond","topic":"Semantic Web and Ontologies","field":"Computer Science","cited_by":3,"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 New Brunswick","funders":"","keywords":"RuleML; Computer science; Semantic Web Rule Language; Information retrieval; OWL-S; Semantic Web Stack; Web Ontology Language; World Wide Web; Semantic Web; XSLT; XML; Ontology; Semantic analytics; Programming language; Markup language; XHTML","score_opus":0.04044158494143771,"score_gpt":0.2615317712698312,"score_spread":0.22109018632839347,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2123328799","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.021759521,0.017639197,0.8943856,0.03122888,0.0018642272,0.004365473,0.00015337468,0.00024783795,0.02835591],"genre_scores_gemma":[0.9907747,0.0005518916,0.0017117073,0.00012130034,0.00005669638,0.00003079001,0.00003303057,0.000015470898,0.006704394],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984631,0.000037900234,0.00063261605,0.00038138643,0.00031362183,0.00017137242],"domain_scores_gemma":[0.9972476,0.0011431852,0.0007060723,0.00057590456,0.0003057848,0.000021495704],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00060158764,0.00025960963,0.0004274266,0.00016321658,0.00015503861,0.00012312208,0.0005493089,0.00020940321,0.0000029617124],"category_scores_gemma":[0.0001632228,0.00014999576,0.00012463755,0.00006458624,0.0005231216,0.00014925592,0.000119856995,0.00014380156,0.0000012795998],"study_design_candidate":"theoretical_or_conceptual","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":[0.000053300715,0.000056589983,0.000112149195,0.0010442861,0.00016283289,0.000003564025,0.0022620035,0.000055113702,0.008023131,0.907768,0.002054468,0.07840455],"study_design_scores_gemma":[0.003912936,0.0014535772,0.047934692,0.0018770098,0.0023198565,0.000114688286,0.0025948551,0.44869167,0.06373906,0.4015643,0.023942927,0.0018544281],"about_ca_topic_score_codex":0.00009515633,"about_ca_topic_score_gemma":0.00019998888,"teacher_disagreement_score":0.9690152,"about_ca_system_score_codex":0.000014610763,"about_ca_system_score_gemma":0.00008406112,"threshold_uncertainty_score":0.61166495},"labels":[],"label_agreement":null},{"id":"W2501175475","doi":"10.1007/978-0-387-34347-1","title":"Canadian Semantic Web","year":2006,"lang":"en","type":"book","venue":"Semantic web and beyond","topic":"Semantic Web and Ontologies","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Université TÉLUQ; Université du Québec à Montréal; Université Laval","funders":"","keywords":"Semantic Web; World Wide Web; Social Semantic Web; Volume (thermodynamics); Computer science; Semantic Web Stack; Physics","score_opus":0.008892958183637823,"score_gpt":0.20891930011763923,"score_spread":0.2000263419340014,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2501175475","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0017699588,0.004855365,0.0011654872,0.0049276343,0.0022101863,0.0006012483,0.00007856857,0.00050092116,0.98389065],"genre_scores_gemma":[0.06681601,0.00047850452,0.0025130124,0.0019515672,0.00073622447,0.000019713218,0.000113186834,0.00009059765,0.9272812],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9963823,0.0000717466,0.0006175109,0.0012204923,0.00058060035,0.001127381],"domain_scores_gemma":[0.9975991,0.00020575747,0.00025107324,0.001318311,0.00013681709,0.0004889086],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00032362292,0.00075045717,0.00094686926,0.0007848837,0.00039562647,0.0005950759,0.0015418375,0.0007189693,0.0000779291],"category_scores_gemma":[0.000043953874,0.00068133214,0.00023717,0.00028279956,0.00025185713,0.00033568297,0.00044819576,0.00062715856,0.00051387923],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000041925773,0.00004900194,0.00073508173,0.00046009917,0.00016012123,0.0012736438,0.00024276141,0.0000047290036,0.00013074058,0.13032363,0.8555572,0.011058791],"study_design_scores_gemma":[0.0007929712,0.00015946166,0.001344452,0.0004119843,0.00021312795,0.00044499326,0.000039146995,0.008765823,0.00004726262,0.066081405,0.920085,0.001614364],"about_ca_topic_score_codex":0.01473218,"about_ca_topic_score_gemma":0.20836253,"teacher_disagreement_score":0.19363035,"about_ca_system_score_codex":0.00028406086,"about_ca_system_score_gemma":0.0031476489,"threshold_uncertainty_score":0.9995638},"labels":[],"label_agreement":null}]}