{"meta":{"query_hash":"3f7fc1108130","filters":{"venue":"Principles of Knowledge Representation and Reasoning"},"cohort_total":18,"direct_labels_cover":0,"predictions_cover":18,"exported":18,"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/3f7fc1108130","api":"https://metacan.xera.ac/api/v1/cohort?venue=Principles+of+Knowledge+Representation+and+Reasoning"},"results":[{"id":"W1510506302","doi":"","title":"Ontologies for dates and duration","year":2010,"lang":"en","type":"article","venue":"Principles of Knowledge Representation and Reasoning","topic":"Semantic Web and Ontologies","field":"Computer Science","cited_by":4,"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 Toronto","funders":"","keywords":"Duration (music); Timeline; Computer science; Ontology; Metric (unit); Mathematics; Statistics","score_opus":0.04243871134609954,"score_gpt":0.3232519904105558,"score_spread":0.28081327906445624,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1510506302","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.87283796,0.00092265697,0.119519204,0.00056636246,0.00039602647,0.00023778426,9.638431e-7,0.000109786306,0.0054092444],"genre_scores_gemma":[0.9043964,0.00011128374,0.09523402,0.0000066821103,0.000034189787,0.000016713408,0.0000028002091,0.0000029476128,0.00019494875],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.99941695,0.000022180307,0.00017896021,0.00022337522,0.00005610285,0.00010241302],"domain_scores_gemma":[0.9991655,0.00039249007,0.00010736385,0.00018950293,0.00010931819,0.000035836503],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002435095,0.000068928304,0.00012654818,0.00006415972,0.00011246383,0.000072464056,0.00015525018,0.000049901595,0.0000016214366],"category_scores_gemma":[0.0009053343,0.000056002566,0.00002388869,0.00007630946,0.000098638964,0.00029778428,0.00015786085,0.00005456959,9.82246e-7],"study_design_candidate":"observational","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":[0.000019192044,0.000047291025,0.12929527,0.0001241465,0.000027971688,0.0000011890027,0.0037320307,0.0000087891285,0.025620438,0.6321346,0.00005583691,0.2089332],"study_design_scores_gemma":[0.0011845186,0.0001338386,0.6379155,0.00009735571,0.000032012693,0.00009042659,0.0013609338,0.23641141,0.10549105,0.010160658,0.0067985887,0.0003236991],"about_ca_topic_score_codex":0.00002462854,"about_ca_topic_score_gemma":0.00016616314,"teacher_disagreement_score":0.621974,"about_ca_system_score_codex":0.0000028469242,"about_ca_system_score_gemma":0.000026878522,"threshold_uncertainty_score":0.22837183},"labels":[],"label_agreement":null},{"id":"W1513254282","doi":"","title":"Towards a logic of feature-based semantic science theories","year":2010,"lang":"en","type":"article","venue":"Principles of Knowledge Representation and Reasoning","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 British Columbia","funders":"","keywords":"Computer science; Feature (linguistics); Artificial intelligence; Epistemology","score_opus":0.02836111487639027,"score_gpt":0.3179121078937459,"score_spread":0.28955099301735565,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1513254282","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7867086,0.00076732633,0.17904714,0.00060040056,0.0006849163,0.0002075281,9.3850286e-7,0.00011493265,0.03186822],"genre_scores_gemma":[0.9306911,0.000023476072,0.069134966,0.000012114209,0.000024242143,0.00000500731,6.9774933e-7,0.0000036121478,0.000104773506],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9989661,0.000046889592,0.000223757,0.00032497378,0.00025390444,0.00018435372],"domain_scores_gemma":[0.998691,0.0002415379,0.00019854469,0.0004530602,0.00034554402,0.00007028584],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007179579,0.00010407047,0.00021648557,0.00021083168,0.00014578493,0.00007110709,0.0006056106,0.00005673085,0.000005750671],"category_scores_gemma":[0.0013362748,0.00007921727,0.00005638845,0.0006494506,0.00073953246,0.00030243956,0.00031845953,0.00012414956,0.0000024336744],"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":[0.0000124377175,0.00007262,0.04237079,0.000102405895,0.000010557602,0.000002785261,0.0018818231,0.000048787537,0.043096688,0.8780067,0.0000052686196,0.034389157],"study_design_scores_gemma":[0.0007372334,0.00011603354,0.36476934,0.00020293756,0.000025244879,0.000047249436,0.00057007675,0.14080088,0.47555825,0.016565572,0.00034480367,0.00026237045],"about_ca_topic_score_codex":0.000048043763,"about_ca_topic_score_gemma":0.00005028305,"teacher_disagreement_score":0.86144114,"about_ca_system_score_codex":0.0000083607565,"about_ca_system_score_gemma":0.00028426707,"threshold_uncertainty_score":0.32303867},"labels":[],"label_agreement":null},{"id":"W1898747386","doi":"","title":"Only-knowing meets nonmonotonic modal logic","year":2012,"lang":"en","type":"article","venue":"Principles of Knowledge Representation and Reasoning","topic":"Logic, Reasoning, and Knowledge","field":"Computer Science","cited_by":9,"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 Toronto","funders":"","keywords":"Non-monotonic logic; Autoepistemic logic; Default logic; Rotation formalisms in three dimensions; Multimodal logic; Dynamic logic (digital electronics); Modal logic; Axiom; Circumscription; Normal modal logic; Computer science; Default; Accessibility relation; Artificial intelligence; Theoretical computer science; Modal operator; Modal; Description logic; Mathematics","score_opus":0.04601614073732518,"score_gpt":0.3090084260364157,"score_spread":0.2629922852990905,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1898747386","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.45648777,0.024863267,0.16529241,0.00044532272,0.0020629524,0.00076414825,0.000003381105,0.0005527504,0.34952798],"genre_scores_gemma":[0.97318876,0.00033623294,0.02413726,0.000025381509,0.00025253123,0.000022727914,0.0000056922836,0.000018803561,0.0020126316],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.9980051,0.00019941614,0.00046624357,0.0005018892,0.00026660837,0.0005607603],"domain_scores_gemma":[0.9983257,0.00032780107,0.00027867508,0.00056046766,0.00020312676,0.00030419827],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000829387,0.00025329227,0.00037843932,0.00021389648,0.00027942244,0.000105559135,0.000565721,0.00013315958,0.000020284315],"category_scores_gemma":[0.00050313905,0.0002183381,0.00015184958,0.00047656204,0.00013161101,0.00096958264,0.000699671,0.00019645558,0.000072475355],"study_design_candidate":"observational","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":[0.000020580574,0.00040107456,0.16860595,0.00013733207,0.000092932605,0.0000069849107,0.011867706,0.00012366303,0.002304955,0.7300126,0.00014037428,0.08628585],"study_design_scores_gemma":[0.0040177107,0.000370304,0.60108835,0.00082591956,0.00019545275,0.00073179614,0.0016395899,0.27730605,0.043344483,0.004305105,0.06405449,0.002120725],"about_ca_topic_score_codex":0.000035359393,"about_ca_topic_score_gemma":0.000023193044,"teacher_disagreement_score":0.7257075,"about_ca_system_score_codex":0.00006908526,"about_ca_system_score_gemma":0.00013615942,"threshold_uncertainty_score":0.8903569},"labels":[],"label_agreement":null},{"id":"W2166645709","doi":"","title":"Horn clause contraction functions: belief set and belief base approaches","year":2010,"lang":"en","type":"article","venue":"Principles of Knowledge Representation and Reasoning","topic":"Logic, Reasoning, and Knowledge","field":"Computer Science","cited_by":34,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Contraction (grammar); Horn clause; Propositional calculus; French horn; Belief revision; Mathematics; Computer science; Algorithm; Artificial intelligence; Discrete mathematics; Logic programming; Linguistics; Psychology","score_opus":0.0617395922315109,"score_gpt":0.28607829287329756,"score_spread":0.22433870064178665,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2166645709","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8328361,0.004496629,0.09323297,0.00051668583,0.001672186,0.0007110022,0.000011530724,0.00039647208,0.06612641],"genre_scores_gemma":[0.9852056,0.00031507295,0.012160873,0.000017790633,0.00022722833,0.000044882407,0.000019795423,0.000017367453,0.0019913923],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99830675,0.00013847838,0.00040866432,0.0006485335,0.000207202,0.00029036257],"domain_scores_gemma":[0.9983209,0.00040613575,0.00028107248,0.0005192507,0.00024171617,0.00023096001],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006995244,0.00022917397,0.00030890075,0.00021843726,0.00039602566,0.0001965566,0.00028526026,0.00017087803,0.000019005289],"category_scores_gemma":[0.0007332826,0.00020159358,0.00008462057,0.00036480816,0.00022768308,0.00074444216,0.0003541344,0.00036020324,0.00002221518],"study_design_candidate":"observational","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":[0.00011286325,0.000827063,0.17590114,0.0003686775,0.00024032753,0.000019384315,0.016305784,0.00012881591,0.01839177,0.4722044,0.0007180878,0.3147817],"study_design_scores_gemma":[0.0054064235,0.00053115276,0.44463077,0.00042091927,0.00025813683,0.0008695327,0.0040831007,0.4540498,0.029695109,0.0042622914,0.05415134,0.0016414345],"about_ca_topic_score_codex":0.00006839215,"about_ca_topic_score_gemma":0.00025493558,"teacher_disagreement_score":0.4679421,"about_ca_system_score_codex":0.000022549648,"about_ca_system_score_gemma":0.00010317015,"threshold_uncertainty_score":0.8220747},"labels":[],"label_agreement":null},{"id":"W2175700267","doi":"","title":"Generalized multi-context systems","year":2014,"lang":"en","type":"article","venue":"Principles of Knowledge Representation and Reasoning","topic":"Logic, Reasoning, and Knowledge","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Operational semantics; Well-founded semantics; Semantics (computer science); Context (archaeology); Computer science; Formal semantics (linguistics); Proof-theoretic semantics; Computational semantics; Denotational semantics; Action semantics; Theoretical computer science; Programming language","score_opus":0.04961093887796212,"score_gpt":0.2983021263901871,"score_spread":0.248691187512225,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2175700267","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":[0.1999248,0.009774039,0.7222134,0.00012397682,0.0015509215,0.0005150527,0.0000020790724,0.00037324362,0.0655225],"genre_scores_gemma":[0.97705317,0.00018264713,0.01878003,0.000018622302,0.00015698091,0.000031231433,0.000005230614,0.000015509047,0.0037565539],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9982334,0.00030780575,0.00045181866,0.00052180537,0.00019754568,0.00028764256],"domain_scores_gemma":[0.9983997,0.00028908649,0.0002903714,0.0005455626,0.00029450105,0.00018082076],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007042776,0.00019842524,0.0003799968,0.00016528954,0.00020710488,0.00016039588,0.000503182,0.000100015735,0.0000064883934],"category_scores_gemma":[0.0006429501,0.00016679808,0.00010700468,0.0003193852,0.00010785243,0.0003559487,0.00038262698,0.00011874868,0.00004020049],"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":[0.000014470328,0.00017392251,0.032173805,0.00016666966,0.00006304255,0.0000034193054,0.0056800325,0.00040227853,0.0016091869,0.8925655,0.00016450493,0.06698315],"study_design_scores_gemma":[0.0020534385,0.00008537322,0.027305642,0.00023559779,0.000027734606,0.00006505466,0.000426234,0.93818694,0.0049884585,0.00035821198,0.025878647,0.00038866836],"about_ca_topic_score_codex":0.00014065258,"about_ca_topic_score_gemma":0.000060428258,"teacher_disagreement_score":0.9377847,"about_ca_system_score_codex":0.00003204281,"about_ca_system_score_gemma":0.00006440596,"threshold_uncertainty_score":0.6801829},"labels":[],"label_agreement":null},{"id":"W2177576448","doi":"","title":"Decidable reasoning in a fragment of the epistemic situation calculus","year":2014,"lang":"en","type":"article","venue":"Principles of Knowledge Representation and Reasoning","topic":"Logic, Reasoning, and Knowledge","field":"Computer Science","cited_by":15,"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 Toronto","funders":"","keywords":"Situation calculus; Decidability; Undecidable problem; Fragment (logic); Calculus (dental); Formalism (music); Computer science; Frame problem; Circumscription; Knowledge representation and reasoning; Mathematics; Theoretical computer science; Artificial intelligence; Algorithm","score_opus":0.022668286495043287,"score_gpt":0.2750889418451013,"score_spread":0.25242065535005803,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2177576448","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.79015726,0.0018851411,0.14950156,0.0002480009,0.0004715328,0.0004935083,0.0000010392428,0.00006721411,0.057174735],"genre_scores_gemma":[0.9916918,0.00008722393,0.007470682,0.000011991143,0.000047301717,0.000025536723,0.000002102285,0.000009929586,0.0006533876],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.998187,0.0003315495,0.00054519833,0.0004114956,0.00027468303,0.00025009492],"domain_scores_gemma":[0.9983172,0.00039901075,0.0004244931,0.00055741693,0.00021901418,0.00008287614],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010780724,0.00015841686,0.00032318212,0.00016587053,0.00014900569,0.000049300368,0.0005407464,0.00009134592,0.0000057171355],"category_scores_gemma":[0.0012977079,0.00011845021,0.000106322026,0.0006670461,0.00012433501,0.0002775997,0.0004981249,0.00015176329,0.0000051911475],"study_design_candidate":"observational","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":[0.00003001346,0.00026876733,0.31639317,0.0002552311,0.000041606752,0.000002018042,0.014823523,0.0022138145,0.0058930255,0.59639066,0.000044832723,0.063643344],"study_design_scores_gemma":[0.0014767258,0.00009241149,0.39023423,0.0010060425,0.000028324635,0.00003380888,0.00052634574,0.5708472,0.03121489,0.0030524177,0.0011921828,0.0002954141],"about_ca_topic_score_codex":0.00018710713,"about_ca_topic_score_gemma":0.00028648818,"teacher_disagreement_score":0.59333825,"about_ca_system_score_codex":0.00007423909,"about_ca_system_score_gemma":0.000120229786,"threshold_uncertainty_score":0.48302594},"labels":[],"label_agreement":null},{"id":"W2189980513","doi":"","title":"Forgetting in action","year":2014,"lang":"en","type":"article","venue":"Principles of Knowledge Representation and Reasoning","topic":"Logic, Reasoning, and Knowledge","field":"Computer Science","cited_by":20,"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 Toronto","funders":"","keywords":"Forgetting; Action (physics); Computer science; Belief revision; Operator (biology); Artificial intelligence; Cognitive science; Calculus (dental); Psychology; Cognitive psychology","score_opus":0.048302891363341906,"score_gpt":0.31641031960924526,"score_spread":0.26810742824590333,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2189980513","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6180753,0.0010506642,0.22855815,0.00018015498,0.00055144954,0.00025106253,3.4003688e-7,0.0001730656,0.15115981],"genre_scores_gemma":[0.98562604,0.000096497715,0.013263302,0.000011553432,0.000091080095,0.000013269472,0.0000022636764,0.000008449538,0.0008875254],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987689,0.00016519641,0.00033140913,0.00037356446,0.00013714097,0.00022375971],"domain_scores_gemma":[0.99898845,0.00030707484,0.00019018003,0.0003127042,0.000116301955,0.0000853171],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00072170055,0.00012292844,0.00022011643,0.00020936402,0.00011304222,0.00006508738,0.0002854365,0.00007153221,0.0000045568518],"category_scores_gemma":[0.000815435,0.0001116515,0.000057307818,0.00041283152,0.000054977787,0.0004317807,0.0002654862,0.00012508007,0.000012069665],"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":[0.000013097404,0.00012602337,0.1881785,0.00013449516,0.00001665619,0.0000025464801,0.0059674093,0.00025342416,0.00303405,0.50659466,0.000035316792,0.2956438],"study_design_scores_gemma":[0.0014009657,0.00010321167,0.3271306,0.00033880665,0.000013507278,0.000047025485,0.0005241512,0.63421357,0.021345846,0.0043475265,0.010147746,0.0003870768],"about_ca_topic_score_codex":0.00004881895,"about_ca_topic_score_gemma":0.00012740759,"teacher_disagreement_score":0.6339601,"about_ca_system_score_codex":0.000034893594,"about_ca_system_score_gemma":0.000043818487,"threshold_uncertainty_score":0.45530158},"labels":[],"label_agreement":null},{"id":"W2200473356","doi":"","title":"Assertion absorption in object queries over knowledge bases","year":2012,"lang":"en","type":"article","venue":"Principles of Knowledge Representation and Reasoning","topic":"Semantic Web and Ontologies","field":"Computer Science","cited_by":7,"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","funders":"","keywords":"Assertion; Computer science; Knowledge base; Object (grammar); Information retrieval; Knowledge-based systems; Base (topology); Knowledge extraction; Absorption (acoustics); Theoretical computer science; Artificial intelligence; Programming language; Mathematics","score_opus":0.04915225042878439,"score_gpt":0.33164701157830595,"score_spread":0.28249476114952154,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2200473356","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9540674,0.0048187296,0.021763878,0.00007157997,0.0004704272,0.00016651828,5.5216276e-7,0.00010560849,0.01853531],"genre_scores_gemma":[0.9927381,0.00026461243,0.0064949426,0.000008069235,0.00007817792,0.000018271197,0.0000046961527,0.000006744144,0.00038633833],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99892455,0.00015104063,0.00031138145,0.00024790844,0.00012249421,0.00024263766],"domain_scores_gemma":[0.999142,0.00029657834,0.00014185409,0.0002579298,0.000088826244,0.000072841765],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005330727,0.000121522055,0.00020586874,0.00021778139,0.00008022395,0.000051107483,0.00018788203,0.00007100055,0.000012499614],"category_scores_gemma":[0.00047001478,0.00010740991,0.000052160034,0.0003634959,0.0000712134,0.0009218651,0.0002192991,0.00008698923,0.000016806538],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000019938774,0.00024204217,0.8261252,0.00011487541,0.0000181057,0.0000016454306,0.011266577,0.000043939668,0.0031485043,0.10997227,0.000051659354,0.04899524],"study_design_scores_gemma":[0.00042939905,0.000030381203,0.9552124,0.00017994168,0.000009453555,0.00001755847,0.000893899,0.02632985,0.014573531,0.0002498044,0.0019109764,0.0001628126],"about_ca_topic_score_codex":0.00012985634,"about_ca_topic_score_gemma":0.00023365124,"teacher_disagreement_score":0.12908718,"about_ca_system_score_codex":0.000042153835,"about_ca_system_score_gemma":0.000054836746,"threshold_uncertainty_score":0.4380049},"labels":[],"label_agreement":null},{"id":"W2222911679","doi":"","title":"Diagnostic problem solving via planning with ontic and epistemic goals","year":2014,"lang":"en","type":"article","venue":"Principles of Knowledge Representation and Reasoning","topic":"AI-based Problem Solving and Planning","field":"Computer Science","cited_by":8,"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 Toronto","funders":"","keywords":"Ontic; Planner; Computer science; Artificial intelligence; Medical diagnosis; Automated planning and scheduling; Machine learning; Epistemology","score_opus":0.01924517497698003,"score_gpt":0.26572870452363717,"score_spread":0.24648352954665714,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2222911679","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":[0.35728666,0.0032298656,0.6297628,0.00024246683,0.00009114415,0.00026735628,7.364465e-7,0.00015536256,0.008963568],"genre_scores_gemma":[0.928319,0.000049767372,0.07129596,0.000015808737,0.0000464171,0.000015746014,0.0000044922003,0.000014077866,0.00023876163],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99860907,0.00016714283,0.00032890338,0.00045470637,0.00017571414,0.00026448767],"domain_scores_gemma":[0.9976185,0.0015629488,0.00026385902,0.00029355646,0.0001222523,0.00013889663],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00069417496,0.00017512249,0.00027676547,0.00014607223,0.00026738903,0.00013787695,0.00023126641,0.0000639832,0.0000019236795],"category_scores_gemma":[0.0005208781,0.00014660922,0.000030148736,0.0002449437,0.00010060524,0.0003630075,0.00022922091,0.00015726958,0.0000034002237],"study_design_candidate":"observational","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":[0.00003199153,0.000067973,0.86432624,0.00069655513,0.000080010985,0.000019460836,0.01551241,0.006220216,0.0017280795,0.03282939,0.00004442585,0.07844327],"study_design_scores_gemma":[0.0015848326,0.00038505893,0.21663451,0.004546132,0.00007887863,0.00035234334,0.00049071765,0.7678666,0.003737996,0.0026737074,0.000978675,0.00067052577],"about_ca_topic_score_codex":0.000062684776,"about_ca_topic_score_gemma":0.000016924803,"teacher_disagreement_score":0.7616464,"about_ca_system_score_codex":0.000019051075,"about_ca_system_score_gemma":0.000053168915,"threshold_uncertainty_score":0.5978551},"labels":[],"label_agreement":null},{"id":"W2237543400","doi":"","title":"Declarative entity resolution via matching dependencies and answer set programs","year":2012,"lang":"en","type":"article","venue":"Principles of Knowledge Representation and Reasoning","topic":"Data Quality and Management","field":"Decision Sciences","cited_by":22,"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 British Columbia; Carleton University","funders":"","keywords":"Computer science; Expressive power; Matching (statistics); Programming language; Set (abstract data type); Theoretical computer science; Invariant (physics); Semantics (computer science); Task (project management); Class (philosophy); Artificial intelligence; Mathematics","score_opus":0.23934077864338069,"score_gpt":0.4310733909013771,"score_spread":0.1917326122579964,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2237543400","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9245435,0.00239615,0.060024004,0.00014838259,0.0003136909,0.000350961,0.000011309146,0.00004221923,0.0121697895],"genre_scores_gemma":[0.9923027,0.00015126198,0.0061880164,0.000014353429,0.00007068693,0.000016086857,0.000027098027,0.0000062618615,0.001223493],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99805474,0.0003818805,0.000479934,0.0003398931,0.00051242515,0.00023114939],"domain_scores_gemma":[0.9985829,0.00046766142,0.00029451953,0.00030366794,0.00020838168,0.0001428949],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003496238,0.00011751986,0.00022735895,0.00016900599,0.00025696654,0.00018274796,0.00019361806,0.000058616613,0.00003318459],"category_scores_gemma":[0.001229875,0.000092262744,0.00005092088,0.0003349496,0.00018804996,0.0011152461,0.0005014954,0.00009788104,0.00002476467],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000086795706,0.00031273536,0.58956945,0.00013329607,0.00010149419,0.0000023773894,0.045860186,0.00007036058,0.0010118373,0.11123287,0.00043687085,0.25118172],"study_design_scores_gemma":[0.0010632899,0.000115977884,0.8704777,0.00025838436,0.00010928272,0.000057396104,0.041381072,0.01415121,0.0033867364,0.014272173,0.054228086,0.0004987387],"about_ca_topic_score_codex":0.00016965212,"about_ca_topic_score_gemma":0.00034160988,"teacher_disagreement_score":0.2809082,"about_ca_system_score_codex":0.000023375433,"about_ca_system_score_gemma":0.000021838498,"threshold_uncertainty_score":0.37623656},"labels":[],"label_agreement":null},{"id":"W2510506392","doi":"","title":"On referring expressions in query answering over first order knowledge bases","year":2016,"lang":"en","type":"article","venue":"Principles of Knowledge Representation and Reasoning","topic":"Natural Language Processing Techniques","field":"Computer Science","cited_by":22,"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","funders":"","keywords":"Computer science; Conjunctive query; Context (archaeology); Noun phrase; Knowledge base; Description logic; Expression (computer science); Class (philosophy); Natural language processing; Artificial intelligence; Information retrieval; Relational database; Programming language; Noun","score_opus":0.03158008085999161,"score_gpt":0.3247805165416627,"score_spread":0.2932004356816711,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2510506392","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6095845,0.01052371,0.3535675,0.0006223749,0.00049483305,0.00052760413,0.0000051376164,0.0007561878,0.023918133],"genre_scores_gemma":[0.93853474,0.00020914202,0.060440533,0.000013728515,0.000039764443,0.000030639356,0.0000011421403,0.000015174752,0.00071511196],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99869597,0.000098419885,0.0003399961,0.00047036092,0.00015809538,0.00023717606],"domain_scores_gemma":[0.9984792,0.00070962816,0.00015879844,0.00042386077,0.00014125108,0.000087265995],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003358494,0.00016464699,0.00022076908,0.00033690818,0.0001323025,0.0000583173,0.00039682904,0.00008504291,0.000016016955],"category_scores_gemma":[0.0012015263,0.00011420461,0.00004596525,0.000492789,0.00007305204,0.00059803587,0.00050787505,0.00013459846,0.000006300502],"study_design_candidate":"bench_or_experimental","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":[0.00012789028,0.00067562144,0.11148301,0.0005832538,0.00005542896,0.00005800789,0.012696891,0.00017123487,0.09128206,0.46319968,0.00039960622,0.31926733],"study_design_scores_gemma":[0.0061938604,0.00043702748,0.16827515,0.030766796,0.00004748943,0.00012846466,0.00071455666,0.12533593,0.6285196,0.022799328,0.0143444,0.0024374125],"about_ca_topic_score_codex":0.000057411336,"about_ca_topic_score_gemma":0.00018506552,"teacher_disagreement_score":0.5372375,"about_ca_system_score_codex":0.00007556493,"about_ca_system_score_gemma":0.00007185231,"threshold_uncertainty_score":0.46571288},"labels":[],"label_agreement":null},{"id":"W2571905942","doi":"","title":"Infinite paths in the situation calculus: axiomatization and properties","year":2016,"lang":"en","type":"article","venue":"Principles of Knowledge Representation and Reasoning","topic":"Formal Methods in Verification","field":"Computer Science","cited_by":2,"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":"Correctness; sort; Situation calculus; Formalism (music); Computer science; Calculus (dental); Futures contract; Natural deduction; Theoretical computer science; Mathematics; Algorithm; Artificial intelligence; Programming language","score_opus":0.06647694693038328,"score_gpt":0.31551713390056374,"score_spread":0.24904018697018046,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2571905942","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.56531,0.00055850676,0.4309347,0.00045481249,0.00008104699,0.00025036695,4.838744e-7,0.00003449044,0.0023756209],"genre_scores_gemma":[0.96469414,0.00024708576,0.03491967,0.000011540309,0.000018104014,0.0000280547,9.773065e-7,0.0000035862238,0.00007686436],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.9990674,0.00025972325,0.0002512135,0.00019268095,0.0001375724,0.00009141023],"domain_scores_gemma":[0.9993029,0.00020206849,0.00014318034,0.00022372791,0.00010381621,0.000024275452],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008576464,0.000068534035,0.00009144221,0.00011820136,0.000082156024,0.000056395933,0.00017975492,0.000036981488,0.0000010166391],"category_scores_gemma":[0.0009221471,0.00003852619,0.000014796858,0.00029250325,0.00008542586,0.0006006441,0.00011568826,0.000038155526,0.000001990117],"study_design_candidate":"observational","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":[0.000020931991,0.000077723365,0.052083574,0.00012902047,0.000011754196,0.0000011182257,0.039660703,0.000064848304,0.03048227,0.45683798,0.0000090017575,0.4206211],"study_design_scores_gemma":[0.0008849167,0.0000795777,0.55936277,0.00061382685,0.000011770536,0.000041172083,0.0014908551,0.3988907,0.035667438,0.0018264682,0.0009105248,0.0002199515],"about_ca_topic_score_codex":0.000018566156,"about_ca_topic_score_gemma":0.00002003526,"teacher_disagreement_score":0.5072792,"about_ca_system_score_codex":0.000018274326,"about_ca_system_score_gemma":0.000027456652,"threshold_uncertainty_score":0.15710524},"labels":[],"label_agreement":null},{"id":"W2572760676","doi":"","title":"Using metric temporal logic to specify scheduling problems","year":2016,"lang":"en","type":"article","venue":"Principles of Knowledge Representation and Reasoning","topic":"Constraint Satisfaction and Optimization","field":"Computer Science","cited_by":2,"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 Toronto","funders":"","keywords":"Temporal logic; Computer science; Linear temporal logic; Formalism (music); Theoretical computer science; Scheduling (production processes); Programming language; Artificial intelligence; Mathematics; Mathematical optimization","score_opus":0.09561138242305982,"score_gpt":0.33751754286274355,"score_spread":0.24190616043968372,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2572760676","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.069534265,0.00026761196,0.9248355,0.00036454867,0.00020373764,0.00020356398,9.678016e-7,0.000082060775,0.004507767],"genre_scores_gemma":[0.73993623,0.00005949677,0.2596743,0.000013205207,0.000037849488,0.000004973992,7.719825e-7,0.000005914732,0.0002672694],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99895114,0.00007445231,0.00031246245,0.0003389249,0.000161253,0.00016174155],"domain_scores_gemma":[0.9991249,0.0001492156,0.00016900923,0.00023328814,0.00019882705,0.00012475059],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00032045858,0.000104959836,0.00016182299,0.00035269116,0.00011651649,0.00006610945,0.00017931925,0.000047015186,0.000024871053],"category_scores_gemma":[0.00043849053,0.00007772754,0.000046794088,0.0007277371,0.000048836733,0.0004058182,0.00021937685,0.0000483544,0.000014262822],"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":[0.000022825625,0.00011635465,0.28651294,0.00010105925,0.000062251005,0.000005798284,0.0029840758,0.023044698,0.028771855,0.21686539,0.00001950091,0.44149324],"study_design_scores_gemma":[0.0020310292,0.0001528104,0.15090889,0.0010460934,0.00003724711,0.00013706114,0.00047285986,0.81434387,0.024827067,0.0020757318,0.0032341597,0.00073320104],"about_ca_topic_score_codex":0.000023470782,"about_ca_topic_score_gemma":0.000021603806,"teacher_disagreement_score":0.79129916,"about_ca_system_score_codex":0.000053873016,"about_ca_system_score_gemma":0.00007230935,"threshold_uncertainty_score":0.31696373},"labels":[],"label_agreement":null},{"id":"W2573027291","doi":"","title":"Negation without negation in probabilistic logic programming","year":2016,"lang":"en","type":"article","venue":"Principles of Knowledge Representation and Reasoning","topic":"Logic, Reasoning, and Knowledge","field":"Computer Science","cited_by":4,"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 British Columbia","funders":"","keywords":"Negation; Probabilistic logic; Computer science; Conditional probability; Mathematics; Joint probability distribution; Algorithm; Theoretical computer science; Artificial intelligence; Algebra over a field; Programming language; Pure mathematics; Statistics","score_opus":0.039872233386709144,"score_gpt":0.302820400739416,"score_spread":0.2629481673527069,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2573027291","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5567088,0.0015443263,0.4084175,0.00066750625,0.00053553405,0.0011538949,0.0000015033105,0.0003420934,0.03062885],"genre_scores_gemma":[0.97553986,0.00011321284,0.023358881,0.000008340824,0.00007024463,0.000066226465,0.0000034909374,0.000011767513,0.00082799915],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.9982692,0.00019880391,0.00048484775,0.00054191175,0.00020949553,0.0002957308],"domain_scores_gemma":[0.99859774,0.00036358106,0.00030000598,0.0003702821,0.000259038,0.00010932692],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006499848,0.00017791163,0.00027352665,0.00024575938,0.000119859484,0.00009225565,0.00032906473,0.00009753228,0.000007775813],"category_scores_gemma":[0.001373366,0.00012459526,0.00006416199,0.00055530627,0.00013806541,0.00069446315,0.0002555967,0.00009466624,0.000018004699],"study_design_candidate":"observational","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":[0.00002955994,0.00020104393,0.2395868,0.00013890541,0.000019264835,0.0000052697305,0.00442449,0.000101684585,0.0029963737,0.41450626,0.000010385354,0.33797997],"study_design_scores_gemma":[0.0059239347,0.00047794188,0.6994034,0.0024416116,0.00006413769,0.00014356332,0.0008227688,0.22296873,0.02021653,0.041315425,0.0049685775,0.0012533724],"about_ca_topic_score_codex":0.00004581595,"about_ca_topic_score_gemma":0.00017636402,"teacher_disagreement_score":0.4598166,"about_ca_system_score_codex":0.00009643052,"about_ca_system_score_gemma":0.00011536072,"threshold_uncertainty_score":0.5080847},"labels":[],"label_agreement":null},{"id":"W2579435387","doi":"","title":"Knowledge compilation for lifted probabilistic inference: compiling to a low-level language","year":2016,"lang":"en","type":"article","venue":"Principles of Knowledge Representation and Reasoning","topic":"Bayesian Modeling and Causal Inference","field":"Computer Science","cited_by":11,"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 British Columbia","funders":"","keywords":"Computer science; Inference; Probabilistic logic; Speedup; Compiler; Relational database; Programming language; Theoretical computer science; Data structure; Artificial intelligence; Data mining; Parallel computing","score_opus":0.09358399773436435,"score_gpt":0.36776521288524194,"score_spread":0.27418121515087757,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2579435387","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":[0.16794865,0.00032326079,0.8285972,0.00021619836,0.00016988852,0.00040684495,0.00001786325,0.000113368835,0.0022067477],"genre_scores_gemma":[0.9394915,0.000022961354,0.059709895,0.000015352416,0.00006884825,0.00006784987,0.000009489695,0.000011907012,0.0006021741],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99865,0.00009440601,0.00040756058,0.00046668042,0.00013712625,0.00024422066],"domain_scores_gemma":[0.9980513,0.0008006288,0.00016070358,0.00035779746,0.00046465982,0.00016490367],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00045362543,0.0001589365,0.00025688068,0.00018074304,0.00014743868,0.00007936159,0.00034787093,0.00007148377,0.0000048267448],"category_scores_gemma":[0.001200012,0.000120083634,0.000064380045,0.00034703655,0.00006985415,0.00028358327,0.00027121577,0.000064669155,0.000018692695],"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":[0.00009371111,0.00031813257,0.012239329,0.00048640286,0.00006203948,0.0000020616762,0.021640891,0.0012306988,0.04016443,0.37040648,0.00010187745,0.55325395],"study_design_scores_gemma":[0.0021415432,0.00027218024,0.038668167,0.002364087,0.000039733597,0.00001643831,0.00049929536,0.9147803,0.032576356,0.0071447073,0.00083246134,0.0006647233],"about_ca_topic_score_codex":0.000014412343,"about_ca_topic_score_gemma":0.000046379657,"teacher_disagreement_score":0.9135496,"about_ca_system_score_codex":0.00004714776,"about_ca_system_score_gemma":0.0001486285,"threshold_uncertainty_score":0.48968685},"labels":[],"label_agreement":null},{"id":"W2898989991","doi":"","title":"On Limited Conjunctions in Polynomial Feature Logics, with Applications in OBDA.","year":2018,"lang":"en","type":"article","venue":"Principles of Knowledge Representation and Reasoning","topic":"Formal Methods in Verification","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 Waterloo","funders":"","keywords":"Computer science; Feature (linguistics); Polynomial; Theoretical computer science; Mathematics; Artificial intelligence; Algebra over a field; Algorithm; Pure mathematics; Linguistics","score_opus":0.040384707731373495,"score_gpt":0.3263807146401066,"score_spread":0.2859960069087331,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2898989991","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":[0.41778466,0.00035886985,0.5278023,0.00037322272,0.0002735072,0.0008454733,0.0000031964,0.00011892725,0.05243987],"genre_scores_gemma":[0.83796847,0.000032117303,0.1615001,0.000018137129,0.000046100733,0.000059873062,0.0000063716657,0.0000063523617,0.00036250154],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.9990903,0.000118930155,0.00021812455,0.00032279608,0.00011095591,0.00013886188],"domain_scores_gemma":[0.99913144,0.0001991676,0.00013778648,0.00034536482,0.00013778584,0.00004844296],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00032913094,0.000096510434,0.00014418081,0.00029318716,0.00009156125,0.000036996415,0.00022604973,0.00006926845,0.0000029207952],"category_scores_gemma":[0.00029040076,0.00008032414,0.000019203368,0.00083942246,0.00014881886,0.00024236037,0.00009858504,0.0001457918,0.000006199762],"study_design_candidate":"observational","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":[0.00015870357,0.00042428504,0.15495077,0.000061651524,0.0000211516,0.000002672163,0.0069172806,0.0007056169,0.0016764868,0.79620296,0.000081999475,0.038796417],"study_design_scores_gemma":[0.0017763511,0.0003989494,0.77235067,0.00036721097,0.0000122075135,0.000025430778,0.0009087598,0.19640726,0.02105054,0.0015864166,0.004762089,0.0003541248],"about_ca_topic_score_codex":0.0000347477,"about_ca_topic_score_gemma":0.00020372335,"teacher_disagreement_score":0.7946166,"about_ca_system_score_codex":0.00005284174,"about_ca_system_score_gemma":0.000062170555,"threshold_uncertainty_score":0.32755235},"labels":[],"label_agreement":null},{"id":"W2899509916","doi":"","title":"Specifying Plausibility Levels for Iterated Belief Change in the Situation Calculus.","year":2018,"lang":"en","type":"article","venue":"Principles of Knowledge Representation and Reasoning","topic":"Logic, Reasoning, and Knowledge","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":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Iterated function; Belief revision; Computer science; Calculus (dental); Situation calculus; Theoretical computer science; Mathematics; Artificial intelligence; Medicine","score_opus":0.15139629189528303,"score_gpt":0.37167727085933766,"score_spread":0.22028097896405463,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2899509916","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.72369576,0.0018195194,0.24657257,0.0005768719,0.0007192331,0.0016089494,0.0000090774265,0.00013035677,0.02486764],"genre_scores_gemma":[0.99141955,0.000042337062,0.007839959,0.00005321992,0.0003322702,0.00009627815,0.00001033145,0.00000875512,0.00019732061],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.99843985,0.00022042594,0.0003992664,0.00047823106,0.00019126931,0.0002709652],"domain_scores_gemma":[0.9983965,0.0005023072,0.00021425416,0.0004290466,0.0003938397,0.00006405071],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013500752,0.00015454993,0.00022926492,0.00015445189,0.00027534633,0.00013031584,0.00045734714,0.00008518737,0.000010254732],"category_scores_gemma":[0.0007763391,0.000113242415,0.00007328328,0.00059723016,0.00014056916,0.00051980367,0.00022574596,0.000109302026,0.000009775244],"study_design_candidate":"observational","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":[0.000109519126,0.000571645,0.14209847,0.00031879262,0.000061026854,0.000007713016,0.19588572,0.000029857545,0.0034024613,0.44475263,0.00016018306,0.21260197],"study_design_scores_gemma":[0.0015601396,0.00024187462,0.65200263,0.0002732978,0.000023049928,0.00003074004,0.0010143394,0.32982326,0.0086249625,0.0020743564,0.004003993,0.00032736294],"about_ca_topic_score_codex":0.00009980395,"about_ca_topic_score_gemma":0.00057695684,"teacher_disagreement_score":0.50990415,"about_ca_system_score_codex":0.00005109013,"about_ca_system_score_gemma":0.00006966648,"threshold_uncertainty_score":0.46178916},"labels":[],"label_agreement":null},{"id":"W3092634028","doi":"","title":"On limited conjunctions in polynomial feature logics, with applications in obda — Extended abstract","year":2018,"lang":"en","type":"article","venue":"Principles of Knowledge Representation and Reasoning","topic":"Logic, Reasoning, and Knowledge","field":"Computer Science","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":"University of Waterloo","funders":"","keywords":"Feature (linguistics); Computer science; Polynomial; Algebra over a field; Theoretical computer science; Mathematics; Artificial intelligence; Pure mathematics; Linguistics; Philosophy","score_opus":0.028799648740481056,"score_gpt":0.29457127866500676,"score_spread":0.2657716299245257,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3092634028","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.78027576,0.0012409724,0.040816046,0.00044133564,0.00040310592,0.0011078825,0.000006307129,0.00021321006,0.17549537],"genre_scores_gemma":[0.9927029,0.00007010303,0.0062336875,0.000022678783,0.00010210616,0.000063677355,0.000012451176,0.000011399842,0.0007809943],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.9986369,0.000083566425,0.0003141134,0.00053833576,0.0001603843,0.00026670273],"domain_scores_gemma":[0.9987052,0.0003523999,0.0001978206,0.00042885906,0.00020951843,0.00010622268],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00030267896,0.00018572147,0.0002690935,0.00037078088,0.00016068698,0.00007581458,0.00033380406,0.00011941601,0.000012536321],"category_scores_gemma":[0.00026781106,0.00014628487,0.00004784373,0.0008760549,0.00021117888,0.00027500512,0.00015579585,0.00024344011,0.00001825008],"study_design_candidate":"observational","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":[0.0004081856,0.0019913719,0.3587583,0.00016921981,0.00009671326,0.00003547318,0.01767412,0.0005593723,0.002855147,0.5560791,0.00054210273,0.060830932],"study_design_scores_gemma":[0.00216722,0.00036006086,0.96299565,0.0003418403,0.00001572077,0.0000341913,0.000820681,0.02235898,0.005118278,0.0013103163,0.0040851664,0.00039189425],"about_ca_topic_score_codex":0.00009056809,"about_ca_topic_score_gemma":0.0011388654,"teacher_disagreement_score":0.6042374,"about_ca_system_score_codex":0.00007334694,"about_ca_system_score_gemma":0.00013169432,"threshold_uncertainty_score":0.5965324},"labels":[],"label_agreement":null}]}