{"meta":{"query_hash":"b5ac7113bb8f","filters":{"venue":"AI Computer Science and Robotics Technology"},"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/b5ac7113bb8f","api":"https://metacan.xera.ac/api/v1/cohort?venue=AI+Computer+Science+and+Robotics+Technology"},"results":[{"id":"W4223609001","doi":"10.5772/acrt.02","title":"MRF Models Based on a Neighborhood Adaptive Class Conditional Likelihood For Multimodal Change Detection","year":2022,"lang":"en","type":"article","venue":"AI Computer Science and Robotics Technology","topic":"Remote-Sensing Image Classification","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Artificial intelligence; Segmentation; Pixel; Change detection; Context (archaeology); Pattern recognition (psychology); Statistical model; Estimator; Bayesian probability; Image segmentation; Markov random field; Modality (human–computer interaction); Markov process; Mathematics; Statistics; Geography","score_opus":0.022469881611816827,"score_gpt":0.22935691942199082,"score_spread":0.206887037810174,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4223609001","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":[0.0065988186,0.000121940444,0.9927181,0.000078162986,0.000009657978,0.000016029266,0.000030166204,0.00015461062,0.0002725244],"genre_scores_gemma":[0.56381303,0.0006054518,0.43060517,0.00023342577,0.00016907218,0.00026099526,0.00041647066,0.00028717832,0.003609232],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993679,0.00023873356,0.00002898192,0.00014682232,0.00015622479,0.00006137819],"domain_scores_gemma":[0.9977315,0.001502322,0.00027209645,0.00018739406,0.00025032158,0.00005626059],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0021881098,0.0005652242,0.0008838704,0.0010937221,0.00032374283,0.0008341677,0.0018668515,0.0013192333,0.0018857403],"category_scores_gemma":[0.006556754,0.00047527315,0.0009350075,0.00084802415,0.000960303,0.0017369401,0.00084645406,0.001335402,0.0006089772],"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":[0.00011168022,0.0000697113,0.0014627557,0.00007252382,0.000083121224,0.000074327625,0.00010881998,0.8644989,0.004065121,0.028515717,0.0010051595,0.09993217],"study_design_scores_gemma":[0.0000019672048,0.0000071125205,0.00015613946,0.0000025874158,0.0000042566453,0.000010988398,0.00000259597,0.99711466,0.00022458579,0.0023025323,0.00016705612,0.0000054841294],"about_ca_topic_score_codex":0.006815293,"about_ca_topic_score_gemma":0.006714197,"teacher_disagreement_score":0.006815293,"about_ca_system_score_codex":0.00077138026,"about_ca_system_score_gemma":0.0007548447,"threshold_uncertainty_score":0.013551235},"labels":[],"label_agreement":null}]}