{"meta":{"query_hash":"5e9e39057333","filters":{"venue":"AHS International Forum 57"},"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/5e9e39057333","api":"https://metacan.xera.ac/api/v1/cohort?venue=AHS+International+Forum+57"},"results":[{"id":"W115772811","doi":"","title":"Army Aviation Fusion of Sensor-Pushed and Agent-Pulled Information","year":2001,"lang":"en","type":"article","venue":"AHS International Forum 57","topic":"Military Defense Systems Analysis","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Lockheed Martin (Canada)","funders":"","keywords":"Aviation; Battle; Sensor fusion; Aeronautics; Systems engineering; Engineering; Computer science; Artificial intelligence; Aerospace engineering","score_opus":0.004737141012470132,"score_gpt":0.19825306630509537,"score_spread":0.19351592529262523,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W115772811","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9729714,0.00013441144,0.011225307,0.00030842476,0.0006188593,0.0001319118,0.00003580675,0.00009109096,0.014482798],"genre_scores_gemma":[0.9986903,0.00018320877,0.00045073417,0.000057366513,0.000050827384,0.00000779367,0.00015248697,0.000008452277,0.00039883266],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999208,0.000013035207,0.00035396707,0.000077603094,0.0002414979,0.00010593396],"domain_scores_gemma":[0.99961996,0.000028530108,0.000070645554,0.00011655627,0.00013017708,0.000034138076],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00011474354,0.00009140785,0.00012756058,0.00022024465,0.000029260993,0.00001741558,0.00008241928,0.000055149012,0.00024282835],"category_scores_gemma":[0.000054362277,0.00009145593,0.00005927281,0.000120939934,0.000013707479,0.00040404117,0.000030776595,0.000056486577,0.00007910484],"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":[0.0005291453,0.00026504992,0.3652662,0.00080100074,0.0034028634,0.000053375246,0.01445528,0.22840755,0.09486231,0.053054534,0.06435749,0.1745452],"study_design_scores_gemma":[0.0021899699,0.000088803994,0.08724302,0.0001480493,0.00010027928,0.00012106364,0.002314813,0.7168969,0.0033153829,0.0017198104,0.18528771,0.0005742181],"about_ca_topic_score_codex":0.00016029157,"about_ca_topic_score_gemma":0.00007488152,"teacher_disagreement_score":0.48848933,"about_ca_system_score_codex":0.000059411028,"about_ca_system_score_gemma":0.0000043158666,"threshold_uncertainty_score":0.37294644},"labels":[],"label_agreement":null}]}