{"meta":{"query_hash":"ce92125df521","filters":{"venue":"International Journal of Services and Operations Management"},"cohort_total":13,"direct_labels_cover":0,"predictions_cover":13,"exported":13,"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/ce92125df521","api":"https://metacan.xera.ac/api/v1/cohort?venue=International+Journal+of+Services+and+Operations+Management"},"results":[{"id":"W1601387675","doi":"10.1504/ijsom.2009.023234","title":"Supplier selection and business process improvement","year":2009,"lang":"en","type":"article","venue":"International Journal of Services and Operations Management","topic":"Quality and Supply Management","field":"Business, Management and Accounting","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":"Olds College","funders":"","keywords":"Humanities; Political science; Business; Philosophy","score_opus":0.007186717907198394,"score_gpt":0.24706663023552008,"score_spread":0.2398799123283217,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1601387675","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":[0.7881003,0.014990006,0.08235002,0.009062075,0.00016696495,0.0004218943,0.0002815812,0.0003776081,0.10424966],"genre_scores_gemma":[0.9894644,0.0018634251,0.0048244027,0.0002018501,0.000049613274,0.00005095288,0.00005862404,0.00001197443,0.0034746535],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9947142,0.0030751613,0.00020589952,0.00041180922,0.0011740301,0.00041891282],"domain_scores_gemma":[0.9608454,0.02605228,0.00813972,0.0007606143,0.002984721,0.001217276],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004954376,0.00043154918,0.000429522,0.0028808222,0.00096876617,0.0023984245,0.00051040214,0.00086609076,0.006701346],"category_scores_gemma":[0.017005304,0.0002631382,0.00050469616,0.005096464,0.0016618202,0.0015402721,0.0017137636,0.00083806284,0.00080401305],"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":[0.00082603906,0.0008309611,0.37398058,0.001598383,0.00046226004,0.0018438394,0.013692916,0.02468226,0.003310155,0.13878171,0.0046873246,0.43530348],"study_design_scores_gemma":[0.0003480206,0.0026234633,0.6423115,0.0010920591,0.00043183594,0.0025810064,0.0122549,0.051581077,0.0034793618,0.22783987,0.055142853,0.00031397742],"about_ca_topic_score_codex":0.004550365,"about_ca_topic_score_gemma":0.0032089544,"teacher_disagreement_score":0.006701346,"about_ca_system_score_codex":0.0035744573,"about_ca_system_score_gemma":0.0033937437,"threshold_uncertainty_score":0.026201606},"labels":[],"label_agreement":null},{"id":"W1979495576","doi":"10.1504/ijsom.2013.056767","title":"Traffic control in Canada-USA border checkpoint operations: impacts on supply chain velocity, infrastructure spending, and national security","year":2013,"lang":"en","type":"article","venue":"International Journal of Services and Operations Management","topic":"Canadian Policy and Governance","field":"Social Sciences","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Wilfrid Laurier University","funders":"","keywords":"Business; Supply chain; Control (management); Harm; Investment (military); Government (linguistics); Order (exchange); National security; Finance; Industrial organization; Economics; Marketing","score_opus":0.005513378612657849,"score_gpt":0.2694225627726871,"score_spread":0.2639091841600293,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1979495576","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":[0.990312,0.000103279344,0.00060975447,0.0008064668,0.0000124217595,0.000032413354,0.0002385392,0.000014432103,0.007870653],"genre_scores_gemma":[0.9984761,0.00009874467,0.000223233,0.000051888946,0.0000016822459,0.0000074907257,0.0001015055,0.0000031208072,0.0010362051],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9992613,0.00011710019,0.000012044903,0.00005642827,0.0001343667,0.00041868974],"domain_scores_gemma":[0.99851376,0.0003513015,0.00026604487,0.000038367845,0.0004919311,0.0003385439],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00060074363,0.00028857673,0.00027627352,0.0006024592,0.0017273353,0.002230043,0.0007263788,0.00068189437,0.002862345],"category_scores_gemma":[0.0037280808,0.00013222745,0.00039394156,0.0012606131,0.0009542802,0.0007073703,0.000999169,0.0010430705,0.00010033623],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010394809,0.0012037914,0.5809202,0.000118155374,0.00026856028,0.0008421285,0.0017973873,0.33919743,0.0034104837,0.028235843,0.007971184,0.034995265],"study_design_scores_gemma":[0.0002281255,0.00077522144,0.74070567,0.00010131267,0.0003041405,0.00014735802,0.025964972,0.20872253,0.0033039164,0.006661056,0.012940039,0.00014567738],"about_ca_topic_score_codex":0.9732887,"about_ca_topic_score_gemma":0.98277885,"teacher_disagreement_score":0.036175307,"about_ca_system_score_codex":0.036175307,"about_ca_system_score_gemma":0.03597965,"threshold_uncertainty_score":0.2624715},"labels":[],"label_agreement":null},{"id":"W2076464241","doi":"10.1504/ijsom.2005.006318","title":"Dynamic analysis of the Newsboy model with early purchase commitments","year":2005,"lang":"en","type":"article","venue":"International Journal of Services and Operations Management","topic":"Supply Chain and Inventory Management","field":"Business, Management and Accounting","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Newsvendor model; Commit; Purchasing; Incentive; Profit (economics); Economic order quantity; Order (exchange); Microeconomics; Computer science; Product (mathematics); Dynamic programming; Operations research; Economics; Business; Operations management; Marketing; Mathematics","score_opus":0.008536362053030433,"score_gpt":0.23215246259953765,"score_spread":0.2236161005465072,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2076464241","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":[0.46815675,0.003970353,0.40125567,0.01036107,0.00050256687,0.00028722384,0.002946183,0.0006862236,0.11183402],"genre_scores_gemma":[0.9358132,0.0011813162,0.0075545455,0.00026073487,0.00013846124,0.00022422391,0.00059938175,0.00013880049,0.05408932],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99932146,0.00016905212,0.000024020745,0.0001159108,0.00010949271,0.0002600304],"domain_scores_gemma":[0.99621046,0.0021432245,0.0007549066,0.00009920813,0.00030132933,0.00049093703],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018128857,0.0014703388,0.0026516253,0.0010722148,0.000984181,0.0036378633,0.0029658068,0.0040857038,0.01782817],"category_scores_gemma":[0.006201844,0.0015089831,0.0015261131,0.0009412272,0.002322399,0.0035738884,0.0018170435,0.0032565284,0.001176562],"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":[0.0002077624,0.00010228292,0.00062153,0.000101578735,0.000051943523,0.00048150908,0.00012965407,0.8725809,0.00057777093,0.12056231,0.002492406,0.0020903687],"study_design_scores_gemma":[0.00005764653,0.000032634063,0.00024854628,0.000012120407,0.00001927151,0.00003097785,0.00006607449,0.97951937,0.00006526218,0.019194568,0.0007263742,0.000027080789],"about_ca_topic_score_codex":0.035140786,"about_ca_topic_score_gemma":0.017982395,"teacher_disagreement_score":0.035140786,"about_ca_system_score_codex":0.0023210933,"about_ca_system_score_gemma":0.0020545206,"threshold_uncertainty_score":0.0698725},"labels":[],"label_agreement":null},{"id":"W2787554693","doi":"10.1504/ijsom.2018.10010643","title":"Coordination and pricing decisions in a closed-loop supply chain","year":2018,"lang":"en","type":"article","venue":"International Journal of Services and Operations Management","topic":"Sustainable Supply Chain Management","field":"Business, Management and Accounting","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":"Wilfrid Laurier University; Seneca Polytechnic","funders":"","keywords":"Supply chain; Business; Closed loop; Loop (graph theory); Industrial organization; Supply chain management; Operations management; Process management; Economics; Marketing; Mathematics","score_opus":0.008016246096019778,"score_gpt":0.2452017391984013,"score_spread":0.23718549310238152,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2787554693","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":[0.8703085,0.00019295822,0.114274725,0.000918336,0.00004273649,0.00011873444,0.000103291175,0.00011414139,0.013926514],"genre_scores_gemma":[0.99558264,0.000059779708,0.002639347,0.000025802998,0.000007733335,0.000020677171,0.00002187236,0.000006825465,0.0016353856],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99747664,0.0009324412,0.00009969173,0.00050719746,0.0003885626,0.000595423],"domain_scores_gemma":[0.99432087,0.0031625177,0.0011496407,0.00026044555,0.0006027775,0.0005037329],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0025800413,0.00054793945,0.0008778458,0.00070256833,0.00099838,0.0035855202,0.0012915394,0.0018861054,0.0052470905],"category_scores_gemma":[0.011395292,0.0008579203,0.0005835457,0.0008217389,0.0024225612,0.003836715,0.0014019054,0.0012130685,0.00047242665],"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":[0.0009138019,0.0005231311,0.011576679,0.00007869396,0.00013527049,0.0010344102,0.0007274543,0.87406534,0.005177166,0.08608363,0.0011072092,0.01857716],"study_design_scores_gemma":[0.00015846477,0.00029984216,0.003493344,0.000015454414,0.000040193187,0.00009855942,0.00048274276,0.9135475,0.0007914803,0.08022617,0.00079300604,0.000053253367],"about_ca_topic_score_codex":0.009950492,"about_ca_topic_score_gemma":0.004381494,"teacher_disagreement_score":0.009950492,"about_ca_system_score_codex":0.0027872715,"about_ca_system_score_gemma":0.0016814197,"threshold_uncertainty_score":0.0202232},"labels":[],"label_agreement":null},{"id":"W2941679361","doi":"10.1504/ijsom.2019.10020831","title":"Hybridising plant propagation and local search for uncapacitated exam scheduling problems","year":2019,"lang":"en","type":"article","venue":"International Journal of Services and Operations Management","topic":"Scheduling and Timetabling Solutions","field":"Decision Sciences","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Metaheuristic; Computer science; Benchmark (surveying); Local search (optimization); Mathematical optimization; Scheduling (production processes); Job shop scheduling; Population; Context (archaeology); Operations research; Artificial intelligence; Mathematics; Geography","score_opus":0.05700839003826297,"score_gpt":0.34046900908351657,"score_spread":0.2834606190452536,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2941679361","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":[0.11654686,0.0016420112,0.87259114,0.00060896255,0.00012617641,0.00015519075,0.0001913773,0.0014001643,0.00673803],"genre_scores_gemma":[0.6621885,0.0005166304,0.332611,0.00034636975,0.00008872898,0.00024788917,0.0004541708,0.00022516861,0.0033216034],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999387,0.0002946117,0.000028165676,0.000086988686,0.00012396243,0.00007918032],"domain_scores_gemma":[0.9974407,0.001985768,0.00018522204,0.00012327451,0.00015694425,0.00010802412],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0019499265,0.0010980451,0.0010309686,0.001151007,0.00036981713,0.0009709311,0.0017987594,0.0012741921,0.0022256307],"category_scores_gemma":[0.004004481,0.0004179968,0.0009767401,0.0012404054,0.0007010708,0.001217974,0.0010879444,0.0013727124,0.00033331724],"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":[0.000054117438,0.00008321302,0.000609369,0.00006888983,0.000039729326,0.000037959446,0.000026529371,0.96031237,0.0006552249,0.0024480475,0.0007269256,0.034937605],"study_design_scores_gemma":[0.000012292319,0.00004018219,0.0000701696,0.0000060923744,0.0000067542633,0.000009485036,0.000009435532,0.99827516,0.00020385308,0.0010564313,0.0003074317,0.000002699095],"about_ca_topic_score_codex":0.0057590236,"about_ca_topic_score_gemma":0.0070635206,"teacher_disagreement_score":0.0057590236,"about_ca_system_score_codex":0.00094706035,"about_ca_system_score_gemma":0.0014493784,"threshold_uncertainty_score":0.011451006},"labels":[],"label_agreement":null},{"id":"W2968770536","doi":"10.1504/ijsom.2019.10023101","title":"An empirical study of the performance of Canadian-owned chains of retail stores","year":2019,"lang":"en","type":"article","venue":"International Journal of Services and Operations Management","topic":"Efficiency Analysis Using DEA","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Laurentian University","funders":"","keywords":"Business; Sample (material); Data envelopment analysis; Retail market; Industrial organization; Retail sales; Retail trade; Marketing; Commerce; Statistics","score_opus":0.04106016820859442,"score_gpt":0.3563887612223212,"score_spread":0.3153285930137268,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2968770536","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":[0.9975151,0.000117162745,0.000106839885,0.000030256087,0.0000011728896,0.000012314979,0.0007831876,0.000003837964,0.0014300684],"genre_scores_gemma":[0.99815255,0.0001389879,0.00015339056,0.0000072535418,0.0000012548645,0.000003645936,0.0010436717,0.0000019898428,0.0004972129],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9986571,0.000060298815,0.000044554894,0.00014765753,0.00060308276,0.0004872557],"domain_scores_gemma":[0.994592,0.00065444096,0.0012297563,0.0002134692,0.0026336522,0.00067657686],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00088453095,0.00033710367,0.00032768364,0.0024726174,0.0019359916,0.0018721848,0.00083197554,0.00032609736,0.0015451668],"category_scores_gemma":[0.004768356,0.00022295544,0.0003731994,0.010613044,0.00093205104,0.00089322263,0.0007780089,0.00044231268,0.0001669994],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001459229,0.00016641349,0.97593147,0.00006378979,0.00008451976,0.00025850936,0.001460353,0.0035430803,0.00085488864,0.0007432499,0.0009795916,0.015768278],"study_design_scores_gemma":[0.0000028647207,0.000059963288,0.99175346,0.000020236386,0.00001853948,0.000058580445,0.0037923602,0.0023734735,0.00026513924,0.000060865594,0.0015777227,0.000016702352],"about_ca_topic_score_codex":0.94686973,"about_ca_topic_score_gemma":0.9697065,"teacher_disagreement_score":0.05313027,"about_ca_system_score_codex":0.022411563,"about_ca_system_score_gemma":0.013765483,"threshold_uncertainty_score":0.16260803},"labels":[],"label_agreement":null},{"id":"W2997916132","doi":"10.1504/ijsom.2020.10026105","title":"Carsharing customer demand forecasting using causal, time series and neural network methods: a case study","year":2020,"lang":"en","type":"article","venue":"International Journal of Services and Operations Management","topic":"Transportation and Mobility Innovations","field":"Engineering","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":"Concordia University","funders":"","keywords":"Exponential smoothing; Demand forecasting; Computer science; Autoregressive integrated moving average; Time series; Artificial neural network; Operations research; Service quality; Customer satisfaction; Service (business); Business; Marketing; Artificial intelligence; Machine learning","score_opus":0.036478361910206696,"score_gpt":0.30528396017292664,"score_spread":0.26880559826271994,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2997916132","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":[0.9801276,0.00027666084,0.016017346,0.0004243875,0.000026549475,0.00008513123,0.00037707415,0.000101813945,0.0025634868],"genre_scores_gemma":[0.99047416,0.00021301502,0.008105857,0.000016685422,0.000012299622,0.000036825128,0.0001988319,0.000008604775,0.0009337554],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99946445,0.00022357248,0.000038812184,0.00006327779,0.00013058604,0.00007922989],"domain_scores_gemma":[0.9967204,0.002473474,0.00015721773,0.00014415763,0.00041184816,0.00009292031],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015095185,0.0006395644,0.00045303084,0.0010440765,0.0006358281,0.0008342381,0.0008997683,0.0016371188,0.0016066043],"category_scores_gemma":[0.0030687645,0.00033327844,0.0006657179,0.0015931291,0.00042437518,0.0009154698,0.000481683,0.0008802385,0.0001582576],"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":[0.00058335945,0.0013926639,0.042009134,0.00029368085,0.000129764,0.0027764447,0.00042211916,0.8912948,0.00236235,0.0040074764,0.0021492646,0.052579015],"study_design_scores_gemma":[0.000019462826,0.00014149782,0.0054189954,0.000006084674,0.000017576056,0.000077501434,0.00026424005,0.9920493,0.0010963158,0.00044727675,0.00044395155,0.000017762814],"about_ca_topic_score_codex":0.04089427,"about_ca_topic_score_gemma":0.034139574,"teacher_disagreement_score":0.04089427,"about_ca_system_score_codex":0.0014689406,"about_ca_system_score_gemma":0.0006565452,"threshold_uncertainty_score":0.08131248},"labels":[],"label_agreement":null},{"id":"W3007959820","doi":"10.1504/ijsom.2020.10027015","title":"Identification and empirical characterisation of flight arrival variation and the impact on departure punctuality","year":2020,"lang":"en","type":"article","venue":"International Journal of Services and Operations Management","topic":"Aviation Industry Analysis and Trends","field":"Economics, Econometrics and Finance","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":"Punctuality; Context (archaeology); Computer science; Variation (astronomy); Identification (biology); Operations research; Econometrics; Transport engineering; Engineering; Mathematics; Geography","score_opus":0.02813310048101605,"score_gpt":0.28147085020882484,"score_spread":0.2533377497278088,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3007959820","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":[0.99606884,0.00015857028,0.0025580307,0.00003214041,0.000008020166,0.0000126541745,0.00039195665,0.000013180226,0.00075651053],"genre_scores_gemma":[0.9989446,0.000038231436,0.00032492937,0.0000039085867,0.000008085838,0.0000060038437,0.0005238191,0.0000030922001,0.00014747145],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9980786,0.0006120388,0.00023860323,0.0003619975,0.00052726694,0.00018146506],"domain_scores_gemma":[0.9657656,0.023794742,0.0064310357,0.001964219,0.0012079364,0.00083643507],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0025441526,0.00029253913,0.00039278492,0.0014679667,0.0001992215,0.0010918509,0.0005827767,0.00049962074,0.0015573055],"category_scores_gemma":[0.013783525,0.00015222495,0.00060680945,0.0019178313,0.0005056127,0.00076948176,0.0005797703,0.0007978871,0.00032699236],"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":[0.00038823273,0.0001650466,0.9693915,0.00007498459,0.00017271088,0.00033361127,0.00044587767,0.011582422,0.0019826426,0.00081313844,0.00016341615,0.0144864395],"study_design_scores_gemma":[0.0000030710353,0.00023441833,0.99086666,0.000008682421,0.000030220006,0.00013488949,0.00036239548,0.00715044,0.00047969967,0.00030604313,0.0004093363,0.000014160807],"about_ca_topic_score_codex":0.0027086355,"about_ca_topic_score_gemma":0.0025977993,"teacher_disagreement_score":0.0027086355,"about_ca_system_score_codex":0.00037033454,"about_ca_system_score_gemma":0.00041087382,"threshold_uncertainty_score":0.013454914},"labels":[],"label_agreement":null},{"id":"W4213180076","doi":"10.1504/ijsom.2007.012136","title":"Fuzzy AHP-based supplier selection in e-procurement","year":2007,"lang":"en","type":"article","venue":"International Journal of Services and Operations Management","topic":"Multi-Criteria Decision Making","field":"Decision Sciences","cited_by":24,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Purchasing; Analytic hierarchy process; Procurement; Computer science; Selection (genetic algorithm); Supplier evaluation; Operations research; Supplier relationship management; Quality (philosophy); Fuzzy logic; Process (computing); Process management; Operations management; Supply chain; Business; Supply chain management; Artificial intelligence; Engineering; Marketing","score_opus":0.053316751949573984,"score_gpt":0.4015697694346537,"score_spread":0.34825301748507975,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4213180076","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":[0.044919234,0.0005346354,0.94712454,0.00038306517,0.00005720916,0.0005148485,0.000082845385,0.0001567276,0.0062268795],"genre_scores_gemma":[0.5620367,0.0004025021,0.43505776,0.0000953938,0.00003227911,0.0005011473,0.000098439945,0.00002330918,0.0017524919],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99399406,0.0041515077,0.00022096462,0.00019516172,0.0012578622,0.0001804882],"domain_scores_gemma":[0.9971437,0.0020669766,0.00014477296,0.000059846952,0.0005071708,0.00007750875],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0065131714,0.00059303996,0.0010264742,0.0017188567,0.0014467604,0.0015447887,0.0012386198,0.00094494084,0.0020464114],"category_scores_gemma":[0.007317671,0.0005524665,0.00062911486,0.0023617079,0.0009280214,0.0011760388,0.0013528906,0.0009144659,0.00025400618],"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":[0.0002383311,0.00017859472,0.0010712986,0.00037294824,0.00012286358,0.0002705306,0.0006664639,0.86093056,0.0018538769,0.024637248,0.0013083122,0.108348966],"study_design_scores_gemma":[0.000039528597,0.00004921994,0.00017276482,0.000033603068,0.00001580356,0.000023423647,0.00013211844,0.9871973,0.0007313293,0.01069782,0.0008918898,0.000015285319],"about_ca_topic_score_codex":0.012308604,"about_ca_topic_score_gemma":0.0123694865,"teacher_disagreement_score":0.012308604,"about_ca_system_score_codex":0.002126466,"about_ca_system_score_gemma":0.0025576341,"threshold_uncertainty_score":0.034445405},"labels":[],"label_agreement":null},{"id":"W4230269512","doi":"10.1504/ijsom.2019.101578","title":"An empirical study of the performance of Canadian-owned chains of retail stores","year":2019,"lang":"en","type":"article","venue":"International Journal of Services and Operations Management","topic":"Efficiency Analysis Using DEA","field":"Decision Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Laurentian University","funders":"","keywords":"Business; Sample (material); Data envelopment analysis; Retail market; Industrial organization; Marketing; Statistics","score_opus":0.04106016820859442,"score_gpt":0.3563887612223212,"score_spread":0.3153285930137268,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4230269512","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":[0.9975151,0.000117162745,0.000106839885,0.000030256087,0.0000011728896,0.000012314979,0.0007831876,0.000003837964,0.0014300684],"genre_scores_gemma":[0.99815255,0.0001389879,0.00015339056,0.0000072535418,0.0000012548645,0.000003645936,0.0010436717,0.0000019898428,0.0004972129],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9986571,0.000060298815,0.000044554894,0.00014765753,0.00060308276,0.0004872557],"domain_scores_gemma":[0.994592,0.00065444096,0.0012297563,0.0002134692,0.0026336522,0.00067657686],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00088453095,0.00033710367,0.00032768364,0.0024726174,0.0019359916,0.0018721848,0.00083197554,0.00032609736,0.0015451668],"category_scores_gemma":[0.004768356,0.00022295544,0.0003731994,0.010613044,0.00093205104,0.00089322263,0.0007780089,0.00044231268,0.0001669994],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001459229,0.00016641349,0.97593147,0.00006378979,0.00008451976,0.00025850936,0.001460353,0.0035430803,0.00085488864,0.0007432499,0.0009795916,0.015768278],"study_design_scores_gemma":[0.0000028647207,0.000059963288,0.99175346,0.000020236386,0.00001853948,0.000058580445,0.0037923602,0.0023734735,0.00026513924,0.000060865594,0.0015777227,0.000016702352],"about_ca_topic_score_codex":0.94686973,"about_ca_topic_score_gemma":0.9697065,"teacher_disagreement_score":0.05313027,"about_ca_system_score_codex":0.022411563,"about_ca_system_score_gemma":0.013765483,"threshold_uncertainty_score":0.16260803},"labels":[],"label_agreement":null},{"id":"W4243583059","doi":"10.1504/ijsom.2020.105373","title":"Identification and empirical characterisation of flight arrival variation and the impact on departure punctuality","year":2020,"lang":"en","type":"article","venue":"International Journal of Services and Operations Management","topic":"Aviation Industry Analysis and Trends","field":"Economics, Econometrics and Finance","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":"Punctuality; Context (archaeology); Variation (astronomy); Computer science; Identification (biology); Econometrics; Operations research; Statistics; Mathematics; Geography","score_opus":0.02813310048101605,"score_gpt":0.28147085020882484,"score_spread":0.2533377497278088,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4243583059","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":[0.99606884,0.00015857028,0.0025580307,0.00003214041,0.000008020166,0.0000126541745,0.00039195665,0.000013180226,0.00075651053],"genre_scores_gemma":[0.9989446,0.000038231436,0.00032492937,0.0000039085867,0.000008085838,0.0000060038437,0.0005238191,0.0000030922001,0.00014747145],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9980786,0.0006120388,0.00023860323,0.0003619975,0.00052726694,0.00018146506],"domain_scores_gemma":[0.9657656,0.023794742,0.0064310357,0.001964219,0.0012079364,0.00083643507],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0025441526,0.00029253913,0.00039278492,0.0014679667,0.0001992215,0.0010918509,0.0005827767,0.00049962074,0.0015573055],"category_scores_gemma":[0.013783525,0.00015222495,0.00060680945,0.0019178313,0.0005056127,0.00076948176,0.0005797703,0.0007978871,0.00032699236],"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":[0.00038823273,0.0001650466,0.9693915,0.00007498459,0.00017271088,0.00033361127,0.00044587767,0.011582422,0.0019826426,0.00081313844,0.00016341615,0.0144864395],"study_design_scores_gemma":[0.0000030710353,0.00023441833,0.99086666,0.000008682421,0.000030220006,0.00013488949,0.00036239548,0.00715044,0.00047969967,0.00030604313,0.0004093363,0.000014160807],"about_ca_topic_score_codex":0.0027086355,"about_ca_topic_score_gemma":0.0025977993,"teacher_disagreement_score":0.0027086355,"about_ca_system_score_codex":0.00037033454,"about_ca_system_score_gemma":0.00041087382,"threshold_uncertainty_score":0.013454914},"labels":[],"label_agreement":null},{"id":"W4247802446","doi":"10.1504/ijsom.2020.104333","title":"Carsharing customer demand forecasting using causal, time series and neural network methods: a case study","year":2020,"lang":"en","type":"article","venue":"International Journal of Services and Operations Management","topic":"Transportation and Mobility Innovations","field":"Engineering","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":"Concordia University","funders":"","keywords":"Exponential smoothing; Demand forecasting; Computer science; Time series; Autoregressive integrated moving average; Artificial neural network; Operations research; Service quality; Customer satisfaction; Service (business); Business; Marketing; Artificial intelligence; Machine learning","score_opus":0.036478361910206696,"score_gpt":0.30528396017292664,"score_spread":0.26880559826271994,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4247802446","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":[0.9801276,0.00027666084,0.016017346,0.0004243875,0.000026549475,0.00008513123,0.00037707415,0.000101813945,0.0025634868],"genre_scores_gemma":[0.99047416,0.00021301502,0.008105857,0.000016685422,0.000012299622,0.000036825128,0.0001988319,0.000008604775,0.0009337554],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99946445,0.00022357248,0.000038812184,0.00006327779,0.00013058604,0.00007922989],"domain_scores_gemma":[0.9967204,0.002473474,0.00015721773,0.00014415763,0.00041184816,0.00009292031],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015095185,0.0006395644,0.00045303084,0.0010440765,0.0006358281,0.0008342381,0.0008997683,0.0016371188,0.0016066043],"category_scores_gemma":[0.0030687645,0.00033327844,0.0006657179,0.0015931291,0.00042437518,0.0009154698,0.000481683,0.0008802385,0.0001582576],"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":[0.00058335945,0.0013926639,0.042009134,0.00029368085,0.000129764,0.0027764447,0.00042211916,0.8912948,0.00236235,0.0040074764,0.0021492646,0.052579015],"study_design_scores_gemma":[0.000019462826,0.00014149782,0.0054189954,0.000006084674,0.000017576056,0.000077501434,0.00026424005,0.9920493,0.0010963158,0.00044727675,0.00044395155,0.000017762814],"about_ca_topic_score_codex":0.04089427,"about_ca_topic_score_gemma":0.034139574,"teacher_disagreement_score":0.04089427,"about_ca_system_score_codex":0.0014689406,"about_ca_system_score_gemma":0.0006565452,"threshold_uncertainty_score":0.08131248},"labels":[],"label_agreement":null},{"id":"W4405000367","doi":"10.1504/ijsom.2024.143066","title":"A simulation-based study to evaluate and improve university parking space","year":2024,"lang":"en","type":"article","venue":"International Journal of Services and Operations Management","topic":"Smart Parking Systems Research","field":"Engineering","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 Regina","funders":"","keywords":"Parking space; Space (punctuation); Computer science; Transport engineering; Engineering; Operating system","score_opus":0.013453246214640812,"score_gpt":0.2972259631974105,"score_spread":0.2837727169827697,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4405000367","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":[0.9905185,0.000059072307,0.0053247027,0.00005771199,0.000019735597,0.00030353825,0.00017722682,0.000072181625,0.0034674269],"genre_scores_gemma":[0.9909422,0.000068052104,0.007982291,0.000013105463,0.000004096539,0.0001664029,0.00020389509,0.000006334282,0.00061362714],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988319,0.00071914995,0.00007860118,0.000097255375,0.00015280733,0.000120261466],"domain_scores_gemma":[0.99453616,0.0035561041,0.00024678017,0.00036831206,0.0009894425,0.00030313918],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002347516,0.0005339623,0.0005825887,0.0009262666,0.0004928955,0.00084553816,0.0007291704,0.00067942514,0.0018859556],"category_scores_gemma":[0.004796125,0.00024931095,0.0006642045,0.00095191004,0.00030665298,0.00074822473,0.00040772933,0.00062941713,0.00019519338],"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":[0.002015632,0.012398194,0.0623917,0.0005190754,0.00037883077,0.00042796347,0.001766381,0.8459367,0.009634493,0.0053799367,0.0019692243,0.05718189],"study_design_scores_gemma":[0.0003171438,0.007294815,0.022183672,0.000056616176,0.00017788052,0.000068437075,0.0017066248,0.9573085,0.0075019705,0.0007751894,0.002545251,0.00006387699],"about_ca_topic_score_codex":0.010737584,"about_ca_topic_score_gemma":0.012209237,"teacher_disagreement_score":0.010737584,"about_ca_system_score_codex":0.0016691819,"about_ca_system_score_gemma":0.0012180302,"threshold_uncertainty_score":0.021350205},"labels":[],"label_agreement":null}]}