{"meta":{"query_hash":"321cfadb3dc6","filters":{"venue":"Research Horizon"},"cohort_total":3,"direct_labels_cover":0,"predictions_cover":3,"exported":3,"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/321cfadb3dc6","api":"https://metacan.xera.ac/api/v1/cohort?venue=Research+Horizon"},"results":[{"id":"W4414618529","doi":"10.54518/rh.5.3.2025.666","title":"Determination of Home Purchase Decisions with Technology Adoption as a Moderating Variable","year":2025,"lang":"en","type":"article","venue":"Research Horizon","topic":"Technology Adoption and User Behaviour","field":"Decision Sciences","cited_by":1,"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":"Purchasing; Moderation; Quarter (Canadian coin); Structural equation modeling; Clothing; Social media; Variables; Variable (mathematics)","score_opus":0.1395683506487525,"score_gpt":0.46441310114462664,"score_spread":0.32484475049587413,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4414618529","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":[0.99880636,0.000035317647,0.00024267206,0.00004726168,0.0000034694333,0.000026037085,0.000056789137,0.0000018957353,0.00078030396],"genre_scores_gemma":[0.9990301,0.000041115145,0.00038616502,0.000016411188,0.0000028805266,0.000032378,0.00007373582,0.000001251643,0.00041596682],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9985362,0.0007964232,0.00010466064,0.00017471687,0.00018487177,0.00020310929],"domain_scores_gemma":[0.9916681,0.0058544744,0.0013188262,0.00030195242,0.00034763958,0.00050889084],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001847871,0.00028712716,0.0003358888,0.00041186498,0.0003811015,0.0009437954,0.00024110587,0.00041757268,0.0040120916],"category_scores_gemma":[0.007057159,0.00021653684,0.00064697175,0.000548832,0.00042474308,0.0005543216,0.0007606438,0.0008641396,0.0003166741],"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":[0.00014974413,0.0004078694,0.99192846,0.00002516039,0.00010364671,0.00008055365,0.00090718665,0.00021070357,0.00045763727,0.0002127664,0.00008238193,0.0054339194],"study_design_scores_gemma":[0.000008387319,0.00030674963,0.9936372,0.000023125267,0.000102294296,0.000054645003,0.0017135664,0.0030769259,0.00046888285,0.00020115865,0.0003985274,0.000008665139],"about_ca_topic_score_codex":0.0065763844,"about_ca_topic_score_gemma":0.010579195,"teacher_disagreement_score":0.0065763844,"about_ca_system_score_codex":0.0005309165,"about_ca_system_score_gemma":0.0007572529,"threshold_uncertainty_score":0.013421714},"labels":[],"label_agreement":null},{"id":"W7083689022","doi":"10.54518/rh.5.2.2025.596","title":"Strengthening Indonesia's Cryptocurrency Regulation to Combat Money Laundering: A Comparative Analysis of Canada and South Korea's Approaches","year":2025,"lang":"en","type":"article","venue":"Research Horizon","topic":"Sentiment Analysis and Opinion Mining","field":"Computer Science","cited_by":1,"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":"Money laundering; Cryptocurrency; Legislation; Asset (computer security); Digital currency; Anonymity; SAFER; Compliance (psychology)","score_opus":0.11398942578506259,"score_gpt":0.34916626180988225,"score_spread":0.23517683602481965,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7083689022","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":[0.94009304,0.001186429,0.00030769213,0.002137288,0.000040545794,0.00007033353,0.00020136207,0.000011474321,0.05595184],"genre_scores_gemma":[0.9949366,0.00089864654,0.00018841148,0.0002693416,0.0000033880249,0.000010724969,0.00010151444,0.000008255249,0.003583105],"study_design_codex":"observational","study_design_gemma":"not_applicable","domain_scores_codex":[0.9986499,0.00018905425,0.00004746226,0.000100854035,0.000498189,0.00051444315],"domain_scores_gemma":[0.99651414,0.00069979276,0.0005063008,0.00008658243,0.0015351801,0.00065807503],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015590629,0.00021263842,0.0002112588,0.0016438218,0.0048402874,0.0042319633,0.0004916,0.0003655583,0.002614272],"category_scores_gemma":[0.0031791076,0.00010824117,0.00020576302,0.0038132549,0.0020000832,0.0012821618,0.0011448511,0.0010503198,0.00015445848],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00081176567,0.0003415616,0.4261225,0.001399005,0.00017826667,0.0038044513,0.21157095,0.0012509351,0.004996049,0.09549385,0.024422714,0.22960807],"study_design_scores_gemma":[0.000024069508,0.00009041121,0.41368264,0.000504303,0.00013779438,0.0003251563,0.4566794,0.0015334979,0.0019965603,0.0009741921,0.12395191,0.000100071506],"about_ca_topic_score_codex":0.83144397,"about_ca_topic_score_gemma":0.9293946,"teacher_disagreement_score":0.16855603,"about_ca_system_score_codex":0.029174503,"about_ca_system_score_gemma":0.042375337,"threshold_uncertainty_score":0.33909738},"labels":[],"label_agreement":null},{"id":"W7127127050","doi":"10.54518/rh.5.6.2025.905","title":"Blue Economy and Corporate Value Creation: A Bibliometric Analysis of Global Research Trends","year":2025,"lang":"","type":"article","venue":"Research Horizon","topic":"Coastal and Marine Management","field":"Environmental Science","cited_by":1,"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":"China; Christian ministry; Scopus; Sustainable development; Resource (disambiguation); Government (linguistics); Natural resource; Public policy; Sustainability","score_opus":0.08552035720353972,"score_gpt":0.39847086823280703,"score_spread":0.3129505110292673,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7127127050","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":[0.7717486,0.09223067,0.0063856975,0.005469837,0.00038554447,0.00055646914,0.05708232,0.0004324565,0.06570832],"genre_scores_gemma":[0.9033271,0.053358506,0.012910139,0.00023123402,0.00041037728,0.0005840396,0.026804632,0.00010542807,0.0022685197],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9904784,0.001679639,0.0019591663,0.0008127801,0.0046004835,0.00046947674],"domain_scores_gemma":[0.9474958,0.03398267,0.008485653,0.0015419223,0.0076171397,0.00087683776],"candidate_categories":["bibliometrics"],"consensus_categories":[],"category_scores_codex":[0.008181217,0.00049677433,0.0010917666,0.1660663,0.0012356609,0.0063302866,0.00055145565,0.0006196281,0.0020490754],"category_scores_gemma":[0.037960194,0.00022737136,0.0010315084,0.2583738,0.00093331735,0.004763234,0.002857837,0.0005374946,0.00045958662],"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":[0.00021526898,0.00012822673,0.4907534,0.016017096,0.0012479803,0.0008443999,0.012124747,0.0024517188,0.0032164247,0.01938246,0.019594008,0.4340242],"study_design_scores_gemma":[0.0000338245,0.00013847652,0.81586164,0.005252654,0.0009684309,0.0012829135,0.016870843,0.005957471,0.0019391074,0.009640226,0.14193335,0.00012107082],"about_ca_topic_score_codex":0.00605221,"about_ca_topic_score_gemma":0.008080507,"teacher_disagreement_score":0.8339337,"about_ca_system_score_codex":0.0023322727,"about_ca_system_score_gemma":0.0049340366,"threshold_uncertainty_score":0.043266892},"labels":[],"label_agreement":null}]}