{"meta":{"query_hash":"0b4c5ec722d5","filters":{"venue":"Technical reports"},"cohort_total":12,"direct_labels_cover":0,"predictions_cover":12,"exported":12,"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/0b4c5ec722d5","api":"https://metacan.xera.ac/api/v1/cohort?venue=Technical+reports"},"results":[{"id":"W1550452056","doi":"10.34989/tr-75","title":"The Bank of Canada's New Quarterly Projection Model, Part 3. The Dynamic Model: QPM","year":2021,"lang":"en","type":"article","venue":"Technical reports","topic":"Monetary Policy and Economic Impact","field":"Economics, Econometrics and Finance","cited_by":81,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Bank of Canada","funders":"","keywords":"Projection (relational algebra); Econometrics; Economics; Computer science; Financial system; Algorithm","score_opus":0.04065913399754401,"score_gpt":0.2297971636475676,"score_spread":0.1891380296500236,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1550452056","genre_codex":"other","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.058665276,0.007960419,0.35163024,0.034666747,0.0017416751,0.0007005392,0.049269244,0.0017478298,0.49361798],"genre_scores_gemma":[0.70353276,0.010602435,0.0959789,0.0013827668,0.00040261899,0.00081829936,0.013206972,0.00056278287,0.17351241],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99915683,0.00018653231,0.00003360601,0.00013752299,0.00034240654,0.00014313104],"domain_scores_gemma":[0.99912566,0.00014200665,0.000069113936,0.00007041643,0.0004764784,0.00011648166],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011455843,0.00064103625,0.00046252686,0.0009334472,0.0018099742,0.0046841716,0.0017355261,0.0011523317,0.01014674],"category_scores_gemma":[0.0037508744,0.0005336135,0.0006007812,0.002208871,0.0011586457,0.0018346502,0.0010059879,0.0016168137,0.0014961781],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000065229266,0.000023688726,0.0048796986,0.00012253944,0.00003360002,0.00014376966,0.00046453872,0.16209698,0.00033053858,0.6887391,0.102715075,0.040385257],"study_design_scores_gemma":[0.000057706075,0.000030545423,0.0084530795,0.00018345231,0.000059933907,0.00013176641,0.00041906795,0.32855546,0.0004407605,0.2583855,0.40316278,0.000119848766],"about_ca_topic_score_codex":0.8697564,"about_ca_topic_score_gemma":0.7768837,"teacher_disagreement_score":0.9798666,"about_ca_system_score_codex":0.020133406,"about_ca_system_score_gemma":0.029560674,"threshold_uncertainty_score":0.26202124},"labels":[],"label_agreement":null},{"id":"W1559784930","doi":"10.34989/tr-95","title":"Essays on Financial Stability","year":2021,"lang":"en","type":"article","venue":"Technical reports","topic":"Global Financial Crisis and Policies","field":"Economics, Econometrics and Finance","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Bank of Canada","funders":"","keywords":"Financial stability; Stability (learning theory); Economics; Finance; Business; Financial system; Computer science; Machine learning","score_opus":0.03654962286200664,"score_gpt":0.24918067607036404,"score_spread":0.2126310532083574,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1559784930","genre_codex":"other","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":[0.0033132327,0.20765653,0.0046755625,0.3373129,0.06837805,0.000066196524,0.00053325226,0.00014890711,0.37791535],"genre_scores_gemma":[0.12909472,0.18954112,0.0045012506,0.089886576,0.12960522,0.0003265058,0.0009198065,0.0003721745,0.4557526],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9980363,0.00068422285,0.00012534329,0.00021604341,0.00071085594,0.00022719496],"domain_scores_gemma":[0.9916688,0.0055438792,0.0005119613,0.00027533795,0.0015626727,0.00043727647],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002787163,0.0011347737,0.00062446226,0.0034203886,0.0036741563,0.0050240876,0.00086609076,0.0031037868,0.01740088],"category_scores_gemma":[0.019736972,0.00024479697,0.00070815545,0.0028860332,0.005110763,0.006189985,0.0023611754,0.004345583,0.0042108325],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000024440715,0.000017244802,0.00022113568,0.00017715301,0.000008985365,0.000087029155,0.0013075361,0.00032309024,0.0000655912,0.2199328,0.7461171,0.031717904],"study_design_scores_gemma":[0.0000045374936,0.00000916779,0.00032197396,0.000407469,0.0000023643365,0.00005259488,0.00046106617,0.000089718014,0.000028074792,0.045759864,0.95285463,0.000008523173],"about_ca_topic_score_codex":0.0040219645,"about_ca_topic_score_gemma":0.0027869681,"teacher_disagreement_score":0.01740088,"about_ca_system_score_codex":0.004518808,"about_ca_system_score_gemma":0.0021487898,"threshold_uncertainty_score":0.058211803},"labels":[],"label_agreement":null},{"id":"W2142123876","doi":"10.34989/tr-79","title":"Measurement of the Output Gap: A Discussion of Recent Research at the Bank of Canada","year":2021,"lang":"en","type":"article","venue":"Technical reports","topic":"Monetary Policy and Economic Impact","field":"Economics, Econometrics and Finance","cited_by":124,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Bank of Canada","funders":"","keywords":"Output gap; Econometrics; Economics; Econometric model; Macroeconomics; Computer science; Monetary policy","score_opus":0.22886368824003694,"score_gpt":0.2994738097182695,"score_spread":0.07061012147823253,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2142123876","genre_codex":"review","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.023372104,0.6946554,0.029426744,0.1510894,0.002257405,0.00020879178,0.004692243,0.00021095133,0.09408702],"genre_scores_gemma":[0.35800862,0.53287995,0.058113806,0.01688785,0.0018300923,0.00032499962,0.002345236,0.00037763998,0.029231839],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9841266,0.003213699,0.00093004457,0.0020508266,0.008290227,0.0013884887],"domain_scores_gemma":[0.9542409,0.012120517,0.002432997,0.0011577883,0.028600542,0.0014472471],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01832265,0.0010675051,0.0015858223,0.011682567,0.006410533,0.010964954,0.0035322388,0.00304116,0.0054151122],"category_scores_gemma":[0.032935087,0.000846859,0.0010630788,0.042170905,0.008656588,0.004954211,0.0024150892,0.003911603,0.0005845376],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":true,"about_ca_system_consensus":true,"study_design_scores_codex":[0.00012554832,0.000087401946,0.039727014,0.0033660196,0.00019339158,0.00020644395,0.004669698,0.0061586807,0.000652089,0.36945236,0.06013164,0.5152297],"study_design_scores_gemma":[0.00005470667,0.000115266615,0.1695139,0.010845515,0.00027780276,0.00028781238,0.011449648,0.009856639,0.0025531347,0.044390045,0.75011444,0.0005410814],"about_ca_topic_score_codex":0.9861247,"about_ca_topic_score_gemma":0.9821255,"teacher_disagreement_score":0.842785,"about_ca_system_score_codex":0.15721501,"about_ca_system_score_gemma":0.13351586,"threshold_uncertainty_score":0.9775111},"labels":[],"label_agreement":null},{"id":"W2226416577","doi":"10.34989/tr-100","title":"ToTEM II: An Updated Version of the Bank of Canada’s Quarterly Projection Model","year":2021,"lang":"en","type":"article","venue":"Technical reports","topic":"Monetary Policy and Economic Impact","field":"Economics, Econometrics and Finance","cited_by":22,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Bank of Canada","funders":"","keywords":"Totem; Projection (relational algebra); Economics; Computer science; Geography; Archaeology; Algorithm","score_opus":0.03601278665655748,"score_gpt":0.21994918236072664,"score_spread":0.18393639570416914,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2226416577","genre_codex":"other","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":[0.030342927,0.003211413,0.2564408,0.018558523,0.0020992102,0.00087093434,0.2436015,0.0033050654,0.4415696],"genre_scores_gemma":[0.38110495,0.007645591,0.1313756,0.0021305722,0.0005825449,0.0013420976,0.14396356,0.0021814236,0.32967356],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99875677,0.00019936354,0.000057185764,0.000180089,0.00057103444,0.00023555913],"domain_scores_gemma":[0.99796534,0.0002225671,0.00010081729,0.00017208759,0.001412744,0.00012658293],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017043995,0.00092244864,0.000703786,0.0013890107,0.001648979,0.0045907055,0.0023458214,0.001110625,0.037961066],"category_scores_gemma":[0.005196132,0.00059019885,0.0008667203,0.0031716046,0.0007495507,0.0020101385,0.0010681801,0.0024073182,0.007378499],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012794095,0.000055032073,0.0059144804,0.00018656017,0.000055377015,0.00019085576,0.0003566888,0.10466899,0.0003256821,0.44186643,0.37992856,0.06632341],"study_design_scores_gemma":[0.000061327235,0.000027998694,0.0066190194,0.00021118112,0.00005000507,0.00013566278,0.0003534518,0.18529783,0.00054637494,0.089805394,0.71674615,0.00014551589],"about_ca_topic_score_codex":0.8943421,"about_ca_topic_score_gemma":0.83888,"teacher_disagreement_score":0.9828033,"about_ca_system_score_codex":0.017196734,"about_ca_system_score_gemma":0.0360893,"threshold_uncertainty_score":0.21256018},"labels":[],"label_agreement":null},{"id":"W2269292283","doi":"10.34989/tr-92","title":"The Performance and Robustness of Simple Monetary Policy Rules in Models of the Canadian Economy","year":2021,"lang":"en","type":"article","venue":"Technical reports","topic":"Monetary Policy and Economic Impact","field":"Economics, Econometrics and Finance","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Bank of Canada","funders":"","keywords":"Simple (philosophy); Output gap; Taylor rule; Monetary policy; Exchange rate; Robustness (evolution); Inflation (cosmology); Economics; Smoothing; Econometrics; Interest rate; Function (biology); Macroeconomic model; Mathematical economics; Computer science; Macroeconomics; Central bank","score_opus":0.04119992220842461,"score_gpt":0.22329044990037902,"score_spread":0.1820905276919544,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2269292283","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":[0.9769116,0.0009645679,0.0076642833,0.00088431494,0.00007753799,0.00017786562,0.0013302463,0.00032881676,0.011660743],"genre_scores_gemma":[0.99411595,0.00052546855,0.0036042966,0.000068851325,0.000016626385,0.000033097287,0.00042499803,0.000030788135,0.001180033],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9978764,0.0007211477,0.00016297596,0.00028908037,0.00051168085,0.0004387859],"domain_scores_gemma":[0.9900603,0.005528111,0.0013400841,0.0008146541,0.0017579102,0.0004989526],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006036843,0.001607726,0.0017441248,0.0015978013,0.0021310202,0.0030792493,0.0028362533,0.0016679419,0.0020885617],"category_scores_gemma":[0.02278628,0.0005827053,0.001175364,0.0016021392,0.0019254476,0.0015778526,0.001192083,0.0014374453,0.00021537305],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002852406,0.00010720686,0.00822933,0.00010888068,0.0001792366,0.00008825377,0.00016094162,0.9767304,0.00054706243,0.007632605,0.0010613875,0.004869395],"study_design_scores_gemma":[0.00022676392,0.000172623,0.0080808345,0.00003883849,0.000169218,0.00003411596,0.00026447902,0.98079634,0.0010982663,0.007604237,0.0014074395,0.0001068385],"about_ca_topic_score_codex":0.82243526,"about_ca_topic_score_gemma":0.7497613,"teacher_disagreement_score":0.9809027,"about_ca_system_score_codex":0.019097302,"about_ca_system_score_gemma":0.0113057615,"threshold_uncertainty_score":0.3572209},"labels":[],"label_agreement":null},{"id":"W2914393718","doi":"10.34989/tr-113","title":"The Framework for Risk Identification and Assessment","year":2021,"lang":"en","type":"article","venue":"Technical reports","topic":"Insurance and Financial Risk Management","field":"Economics, Econometrics and Finance","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Bank of Canada","funders":"","keywords":"Financial stability; Identification (biology); Suite; Resilience (materials science); Business; Risk assessment; Financial risk; Component (thermodynamics); Psychological resilience; Risk analysis (engineering); Financial system; Finance; Computer science; Geography; Computer security","score_opus":0.025771960317341833,"score_gpt":0.2878304577695239,"score_spread":0.262058497452182,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2914393718","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00067003054,0.0013011055,0.96211606,0.004764968,0.00018393404,0.00012774659,0.00042277685,0.00020983382,0.030203555],"genre_scores_gemma":[0.17700072,0.0066993763,0.77835155,0.0019909204,0.0013881132,0.0017527603,0.0010261821,0.0003367704,0.031453542],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9910439,0.0042494787,0.0005885563,0.0009864817,0.0026444963,0.00048706806],"domain_scores_gemma":[0.9901765,0.0054802177,0.00078050065,0.0011487523,0.0020576427,0.0003564638],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.010480468,0.0024056241,0.00167072,0.0031839544,0.0017861114,0.0075426954,0.0045458656,0.0045399335,0.011786154],"category_scores_gemma":[0.017704602,0.0010895074,0.0030666427,0.0024640418,0.0055074114,0.0060280226,0.004349325,0.006517403,0.003708484],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000003440199,0.00001121287,0.00014144531,0.000045256525,0.000022109463,0.00004415759,0.00007584847,0.019084632,0.000056185097,0.96969056,0.003403755,0.0074214293],"study_design_scores_gemma":[0.000008028374,0.000009863916,0.0000712304,0.00008306642,0.000012235588,0.000058860067,0.00004438764,0.053496208,0.00005372452,0.9151427,0.0310017,0.000017953394],"about_ca_topic_score_codex":0.020467535,"about_ca_topic_score_gemma":0.009100994,"teacher_disagreement_score":0.020467535,"about_ca_system_score_codex":0.006117977,"about_ca_system_score_gemma":0.0079980595,"threshold_uncertainty_score":0.055426657},"labels":[],"label_agreement":null},{"id":"W2936076545","doi":"10.34989/tr-115","title":"Bond Funds and Fixed-Income Market Liquidity: A Stress-Testing Approach","year":2021,"lang":"en","type":"article","venue":"Technical reports","topic":"Market Dynamics and Volatility","field":"Economics, Econometrics and Finance","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Bank of Canada","funders":"","keywords":"Fixed income; Market liquidity; Bond market; Bond; Monetary economics; Stress testing (software); Global assets under management; Economics; Business; Financial system; Finance; Institutional investor; Computer science","score_opus":0.03388485045101362,"score_gpt":0.2355869126760687,"score_spread":0.2017020622250551,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2936076545","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":[0.17258647,0.001408227,0.8033374,0.003023273,0.00016818424,0.00012358437,0.000469066,0.00041039748,0.018473413],"genre_scores_gemma":[0.968978,0.00094609236,0.023213882,0.0001860573,0.0003774301,0.00016661201,0.00024460527,0.000057449248,0.005829918],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984504,0.0009462738,0.000055864904,0.0001498754,0.00020344988,0.00019424288],"domain_scores_gemma":[0.9908309,0.0067816423,0.0008039207,0.00063276064,0.00057160744,0.00037931727],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0049637686,0.0012750257,0.0012139601,0.002005993,0.0006273629,0.0026309295,0.0015192905,0.0021753998,0.005163154],"category_scores_gemma":[0.023724224,0.0005241458,0.0010437956,0.0011330987,0.0024038476,0.003974383,0.002017622,0.0022904477,0.00038912243],"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":[0.00034740535,0.00014898945,0.013707487,0.00009890444,0.00015780274,0.000497216,0.00022237588,0.2000711,0.0014369433,0.7237454,0.002286124,0.057280276],"study_design_scores_gemma":[0.00004870766,0.00009969385,0.0016833233,0.000027551238,0.00003517417,0.000077529774,0.00008555239,0.64805937,0.0005546904,0.34824628,0.0010489828,0.00003312271],"about_ca_topic_score_codex":0.003452626,"about_ca_topic_score_gemma":0.0015893755,"teacher_disagreement_score":0.005163154,"about_ca_system_score_codex":0.0007559774,"about_ca_system_score_gemma":0.0011041973,"threshold_uncertainty_score":0.026251256},"labels":[],"label_agreement":null},{"id":"W3012348751","doi":"10.34989/tr-116","title":"IMPACT: The Bank of Canada’s International Model for Projecting Activity","year":2020,"lang":"en","type":"article","venue":"Technical reports","topic":"Monetary Policy and Economic Impact","field":"Economics, Econometrics and Finance","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Bank of Canada","funders":"","keywords":"Consistency (knowledge bases); Balance of trade; Economics; China; Stock (firearms); Capital flows; Stock market; Economy; International trade; Geography; Computer science; Market economy","score_opus":0.12428844612947763,"score_gpt":0.28103687943129657,"score_spread":0.15674843330181892,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3012348751","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.029026346,0.0015981268,0.37246048,0.01826938,0.0007283154,0.0005302074,0.04020386,0.0020902893,0.53509295],"genre_scores_gemma":[0.65667945,0.00502295,0.19093877,0.0011094206,0.00021081766,0.0013330008,0.023736645,0.0011311736,0.11983774],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990711,0.00019158932,0.000030232302,0.00011509626,0.00039503543,0.0001968082],"domain_scores_gemma":[0.9988979,0.00013510163,0.00007960581,0.00010481085,0.00065230584,0.000130175],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011274988,0.0010316652,0.0005432169,0.0017480371,0.0019950466,0.00506477,0.0028277794,0.0014454494,0.015247369],"category_scores_gemma":[0.0035633317,0.0005739171,0.0010352401,0.0037649057,0.001570268,0.0024068947,0.0015188884,0.002389511,0.0021041348],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003920524,0.00002264978,0.0038346827,0.00005718731,0.00003382847,0.0000713782,0.00030787225,0.19726442,0.000107526845,0.7301671,0.047150373,0.020943798],"study_design_scores_gemma":[0.00006167841,0.000024032384,0.0038108162,0.00014195825,0.000046183053,0.00008727805,0.0003616745,0.4720109,0.0003220423,0.2472965,0.27573004,0.00010684081],"about_ca_topic_score_codex":0.89558226,"about_ca_topic_score_gemma":0.8241903,"teacher_disagreement_score":0.89558226,"about_ca_system_score_codex":0.021785667,"about_ca_system_score_gemma":0.038612083,"threshold_uncertainty_score":0.2100653},"labels":[],"label_agreement":null},{"id":"W3121666479","doi":"10.34989/tr-84","title":"Yield Curve Modelling at the Bank of Canada","year":2021,"lang":"en","type":"article","venue":"Technical reports","topic":"Monetary Policy and Economic Impact","field":"Economics, Econometrics and Finance","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Bank of Canada","funders":"","keywords":"Yield curve; Coupon; Econometrics; Parametric model; Parametric statistics; Interest rate; Model selection; Function (biology); Government debt; Set (abstract data type); Economics; Computer science; Debt; Estimation; Mathematical optimization; Mathematics; Finance; Statistics","score_opus":0.08614485737728451,"score_gpt":0.2205507516340795,"score_spread":0.134405894256795,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3121666479","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.24931172,0.0044330144,0.4011271,0.006976109,0.00035272224,0.00044809104,0.05516435,0.004616957,0.27756998],"genre_scores_gemma":[0.8579214,0.0030005856,0.061571326,0.000196157,0.00004178866,0.00017620919,0.013755143,0.0004284998,0.06290886],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99899834,0.000085533626,0.000042446813,0.00019851654,0.00054404687,0.00013125021],"domain_scores_gemma":[0.9983758,0.00017090971,0.00013464998,0.00014276024,0.0011083916,0.00006748521],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013035863,0.0007438344,0.00042193857,0.0015638957,0.0012239534,0.003309633,0.0016331341,0.0007957584,0.006707128],"category_scores_gemma":[0.0043871575,0.0004123266,0.00059360487,0.0039112587,0.0007477949,0.0013981049,0.00066552375,0.00090225966,0.001082886],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015194506,0.000047011297,0.021729363,0.00019687413,0.000054584267,0.00025108334,0.0007292963,0.56068,0.0024021843,0.27530473,0.040414907,0.09803805],"study_design_scores_gemma":[0.000024440895,0.000026981459,0.019090442,0.00011691188,0.000042458687,0.00010215846,0.00037653692,0.8434914,0.0028884974,0.02489083,0.10883385,0.00011544539],"about_ca_topic_score_codex":0.9519544,"about_ca_topic_score_gemma":0.90197873,"teacher_disagreement_score":0.048045576,"about_ca_system_score_codex":0.025373656,"about_ca_system_score_gemma":0.024147462,"threshold_uncertainty_score":0.18409961},"labels":[],"label_agreement":null},{"id":"W3123097938","doi":"10.34989/tr-99","title":"Introducing the Bank of Canada's Projection Model for the Global Economy","year":2021,"lang":"en","type":"article","venue":"Technical reports","topic":"Monetary Policy and Economic Impact","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":true,"ca_institutions":"Bank of Canada","funders":"","keywords":"Projection (relational algebra); Complement (music); Economy; Set (abstract data type); Economics; Business; Computer science; Algorithm","score_opus":0.05142421724296939,"score_gpt":0.24208456970910674,"score_spread":0.19066035246613736,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3123097938","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.02425261,0.0039038647,0.59091765,0.023772478,0.0013886391,0.00039625497,0.01382618,0.0014547859,0.34008753],"genre_scores_gemma":[0.6793877,0.0074624317,0.21217318,0.002123304,0.0004643134,0.00082166994,0.0061262585,0.00075206044,0.09068913],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991654,0.00020645473,0.000024828578,0.00012626825,0.00033970142,0.00013742008],"domain_scores_gemma":[0.9992161,0.000111764486,0.000047072717,0.00007614331,0.00045134782,0.00009757228],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013614447,0.0008801,0.0005445217,0.0011943147,0.0016478687,0.0035709806,0.0017798243,0.0014235793,0.0077617],"category_scores_gemma":[0.0031715038,0.00050029845,0.0009088087,0.002592985,0.0015068873,0.0022420797,0.002082612,0.002608007,0.0011978773],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000023069764,0.000009893892,0.0013845563,0.0000424131,0.00002365325,0.00010780872,0.0002062795,0.11852848,0.00017483972,0.8423262,0.02355943,0.013613318],"study_design_scores_gemma":[0.000059893973,0.000024733305,0.0024579724,0.00011699817,0.00003283268,0.00010746527,0.00021507233,0.3851252,0.0003165093,0.41548446,0.19594839,0.00011048456],"about_ca_topic_score_codex":0.80786467,"about_ca_topic_score_gemma":0.7620122,"teacher_disagreement_score":0.9856233,"about_ca_system_score_codex":0.014376719,"about_ca_system_score_gemma":0.026746655,"threshold_uncertainty_score":0.38653368},"labels":[],"label_agreement":null},{"id":"W3123135674","doi":"","title":"Analyzing and Forecasting the Canadian Economy through the LENS Model","year":2014,"lang":"en","type":"article","venue":"Technical reports","topic":"Monetary Policy and Economic Impact","field":"Economics, Econometrics and Finance","cited_by":4,"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":"Projection (relational algebra); Through-the-lens metering; Totem; Lens (geology); Economics; Economic model; Key (lock); Economy; Set (abstract data type); Macroeconomic model; Complement (music); Econometrics; Empirical research; Empirical modelling; Macroeconomics; Computer science; Geography; Engineering; Mathematics; Algorithm; Statistics; Simulation","score_opus":0.1242704258442306,"score_gpt":0.24066873583756454,"score_spread":0.11639830999333393,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3123135674","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":[0.32015365,0.0029462469,0.4594788,0.015836151,0.00046599924,0.00038333793,0.019867148,0.0021923943,0.17867635],"genre_scores_gemma":[0.8930606,0.0018249567,0.07702111,0.00038485217,0.00008745001,0.0001332044,0.0041954136,0.00014381486,0.023148596],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996126,0.000055976037,0.000012540477,0.00007384906,0.00013898482,0.00010616664],"domain_scores_gemma":[0.9991861,0.00017139035,0.00006687227,0.000053396947,0.00044398967,0.00007830772],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007888877,0.0006306553,0.0003944613,0.001567746,0.0012254606,0.002643465,0.0011438221,0.00058584614,0.0048109917],"category_scores_gemma":[0.0036929687,0.0002963027,0.0007008497,0.001976326,0.0008299003,0.001500597,0.0011607419,0.0009051054,0.00046248545],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010892519,0.000024544248,0.0135639515,0.00007460938,0.00007219592,0.00013034289,0.0004748677,0.6323472,0.00055105507,0.2816719,0.019012995,0.051967274],"study_design_scores_gemma":[0.000021688405,0.000012209331,0.00460871,0.000026210182,0.000029964416,0.00001704126,0.00021461675,0.9466209,0.00026559347,0.031059332,0.017078893,0.000044724577],"about_ca_topic_score_codex":0.9576293,"about_ca_topic_score_gemma":0.9317338,"teacher_disagreement_score":0.042370677,"about_ca_system_score_codex":0.021170845,"about_ca_system_score_gemma":0.017127514,"threshold_uncertainty_score":0.15360594},"labels":[],"label_agreement":null},{"id":"W3174615909","doi":"10.34989/tr-119","title":"ToTEM III: The Bank of Canada’s Main DSGE Model for Projection and Policy Analysis","year":2021,"lang":"en","type":"article","venue":"Technical reports","topic":"Monetary Policy and Economic Impact","field":"Economics, Econometrics and Finance","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Bank of Canada","funders":"","keywords":"Totem; Humanities; Political science; Physics; Economy; Economics; Geography; Art; Archaeology","score_opus":0.05527731653171323,"score_gpt":0.25164396522778165,"score_spread":0.19636664869606843,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3174615909","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.017021379,0.003340203,0.42256922,0.015200801,0.0015324887,0.00066148443,0.11969331,0.0062970277,0.41368413],"genre_scores_gemma":[0.37260133,0.006740892,0.22850506,0.002768449,0.00058527046,0.0019126569,0.09733386,0.006879517,0.2826729],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992187,0.00017544458,0.000024705141,0.00009473312,0.00032549747,0.00016090751],"domain_scores_gemma":[0.99909997,0.00008930405,0.0000520071,0.00007892262,0.000572064,0.000107689615],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011160307,0.0012643419,0.0010512152,0.000966038,0.0019007446,0.004124901,0.0025485223,0.00137008,0.022997117],"category_scores_gemma":[0.0029819203,0.0008458731,0.0012372155,0.0017008415,0.00096998847,0.0014495364,0.001601328,0.00297443,0.0052450127],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014051756,0.000028599487,0.0023242228,0.00018492647,0.00014716048,0.00018409838,0.00026365343,0.25384894,0.0007329733,0.36263436,0.34815177,0.031358775],"study_design_scores_gemma":[0.0001286209,0.000022544293,0.003000414,0.00022607473,0.00009943926,0.00010568258,0.00017552692,0.4136176,0.0007807731,0.10984045,0.47180733,0.00019542863],"about_ca_topic_score_codex":0.8950348,"about_ca_topic_score_gemma":0.8450702,"teacher_disagreement_score":0.9855019,"about_ca_system_score_codex":0.014498135,"about_ca_system_score_gemma":0.03548735,"threshold_uncertainty_score":0.21116668},"labels":[],"label_agreement":null}]}