{"meta":{"query_hash":"44d9f00538ae","filters":{"venue":"International journal of advanced research in humanities and law."},"cohort_total":1,"direct_labels_cover":0,"predictions_cover":1,"exported":1,"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/44d9f00538ae","api":"https://metacan.xera.ac/api/v1/cohort?venue=International+journal+of+advanced+research+in+humanities+and+law."},"results":[{"id":"W4408557531","doi":"10.63053/ijrel.44","title":"The Role of Artificial Intelligence in Reducing Environmental Impacts in The Oil and Gas Industry from A Legal Perspective: A Comparative and Case Study","year":2025,"lang":"en","type":"article","venue":"International journal of advanced research in humanities and law.","topic":"Digital Transformation in Law","field":"Economics, Econometrics and Finance","cited_by":0,"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":"Perspective (graphical); Petroleum industry; Environmental impact assessment; Business; Engineering; Management science; Artificial intelligence; Political science; Computer science; Law; Environmental engineering","score_opus":0.09963252560514958,"score_gpt":0.3750823676425315,"score_spread":0.27544984203738193,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4408557531","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":[0.7545092,0.0039983136,0.005046344,0.0055469144,0.00006691494,0.00023955622,0.000073917916,0.000025705565,0.23049302],"genre_scores_gemma":[0.98834306,0.0034840137,0.002817575,0.00032893056,0.000026387937,0.00008430203,0.000037550773,0.0000081613825,0.00487013],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"qualitative","domain_scores_codex":[0.9953002,0.0029298344,0.00011626673,0.00015251088,0.0009819418,0.0005192721],"domain_scores_gemma":[0.9941789,0.0041625146,0.00058384,0.00023487333,0.00062933005,0.00021060015],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004895061,0.0003409279,0.0002784058,0.0030692723,0.004207533,0.005293091,0.0013303852,0.003139354,0.0028101213],"category_scores_gemma":[0.0069524487,0.00017730401,0.00043060925,0.004327311,0.005057375,0.003655641,0.0026297236,0.0014685679,0.00024395308],"study_design_candidate":"qualitative","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":[0.00027070084,0.0024091147,0.06567062,0.0016083242,0.000095199044,0.017372731,0.07610964,0.016928447,0.0022708245,0.6432442,0.011886564,0.16213374],"study_design_scores_gemma":[0.000093831564,0.0012751694,0.089774035,0.0024019426,0.00016822696,0.0048697917,0.50306785,0.030826455,0.006553636,0.050330956,0.31051445,0.00012364914],"about_ca_topic_score_codex":0.01584084,"about_ca_topic_score_gemma":0.024841664,"teacher_disagreement_score":0.01584084,"about_ca_system_score_codex":0.0075640036,"about_ca_system_score_gemma":0.0039961804,"threshold_uncertainty_score":0.054880977},"labels":[],"label_agreement":null}]}