{"meta":{"query_hash":"659492be3190","filters":{"venue":"International Journal of Robotic Computing"},"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/659492be3190","api":"https://metacan.xera.ac/api/v1/cohort?venue=International+Journal+of+Robotic+Computing"},"results":[{"id":"W3174973594","doi":"10.35708/rc1869-126260","title":"Identifying Hazardous Shapes in the Plane","year":2020,"lang":"en","type":"article","venue":"International Journal of Robotic Computing","topic":"Optimization and Search Problems","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":"Carleton University","funders":"","keywords":"Robot; Vertex (graph theory); Regular polygon; Line segment; Mobile robot; Hazardous waste; A priori and a posteriori; Enhanced Data Rates for GSM Evolution; Line (geometry); Computer science; Plane (geometry); Set (abstract data type); Artificial intelligence; Combinatorics; Mathematics; Algorithm; Engineering; Geometry; Graph","score_opus":0.05499822655337135,"score_gpt":0.3129449552881545,"score_spread":0.2579467287347832,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3174973594","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":[0.006209589,0.00009552225,0.9689836,0.0236791,0.000530789,0.00004696812,1.7116452e-7,0.000015797728,0.00043845797],"genre_scores_gemma":[0.9465163,0.000014383159,0.05079434,0.0023690956,0.0002957936,1.7395321e-7,4.7381226e-7,0.0000033298154,0.000006128161],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99863464,0.00010571232,0.00040253016,0.00010615783,0.0006262002,0.00012475929],"domain_scores_gemma":[0.99920946,0.00022663937,0.0002327468,0.000059493235,0.00021522104,0.000056464578],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006276188,0.000063781335,0.000113515765,0.00012821307,0.000044980145,0.00038023427,0.0014237919,0.00001794732,0.000015574185],"category_scores_gemma":[0.00019026146,0.00004667323,0.0000636772,0.00023440798,0.000015913649,0.0003329043,0.00020767962,0.00026488389,0.000013222445],"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":[0.000011277027,0.000055593286,0.001348133,0.000008328244,0.000047100464,0.00061369897,0.009180397,0.9436285,0.00023102906,0.013953494,0.00079569715,0.03012678],"study_design_scores_gemma":[0.00046396203,0.00006063223,0.003463023,0.00008022655,0.0000025485112,0.00046256764,0.0002614887,0.99359787,0.000039470466,0.0009906599,0.00051110325,0.00006647785],"about_ca_topic_score_codex":0.0000057695697,"about_ca_topic_score_gemma":0.000002020243,"teacher_disagreement_score":0.94030666,"about_ca_system_score_codex":0.00003200905,"about_ca_system_score_gemma":0.00006318602,"threshold_uncertainty_score":0.36666077},"labels":[],"label_agreement":null}]}