{"meta":{"query_hash":"57d647f7f4c6","filters":{"venue":"AIAA SPACE and Astronautics Forum and Exposition"},"cohort_total":2,"direct_labels_cover":0,"predictions_cover":2,"exported":2,"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/57d647f7f4c6","api":"https://metacan.xera.ac/api/v1/cohort?venue=AIAA+SPACE+and+Astronautics+Forum+and+Exposition"},"results":[{"id":"W2755658620","doi":"10.2514/6.2017-5145","title":"Innovative Test Operations to Support Orion and Future Human Rated Missions","year":2017,"lang":"en","type":"article","venue":"AIAA SPACE and Astronautics Forum and Exposition","topic":"Spacecraft Design and Technology","field":"Engineering","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":"Lockheed Martin (Canada)","funders":"","keywords":"Test (biology); Computer science; Aeronautics; Engineering; Systems engineering; Geology","score_opus":0.008720543081462516,"score_gpt":0.24594525461725372,"score_spread":0.2372247115357912,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2755658620","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":[0.28618765,0.002374819,0.5007274,0.0049253264,0.001031533,0.0009800554,0.00064785464,0.007083429,0.19604196],"genre_scores_gemma":[0.7596862,0.0009624244,0.2070579,0.0008082348,0.00020835684,0.0003889735,0.0009205312,0.00042708038,0.029540276],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9981541,0.00037359464,0.00005152492,0.00010429106,0.0011269763,0.00018949527],"domain_scores_gemma":[0.9979912,0.00024127084,0.0002464625,0.00038304273,0.0008722515,0.00026569373],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0033411726,0.0005074704,0.00023014678,0.00076689763,0.00084762153,0.0011664467,0.0012272671,0.0005989105,0.00508693],"category_scores_gemma":[0.0020275742,0.00016566178,0.00027998586,0.00030424935,0.0006722875,0.0014818382,0.0017542262,0.0008794985,0.0011367671],"study_design_candidate":"bench_or_experimental","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":[0.0010072245,0.0007153062,0.017313924,0.0003399268,0.000054953718,0.0009087392,0.0022401114,0.020519378,0.13885817,0.051448487,0.03227926,0.7343145],"study_design_scores_gemma":[0.0004357467,0.006118167,0.04019937,0.00038600375,0.00008750245,0.0033837243,0.0027055652,0.06166616,0.11795139,0.025384191,0.7414646,0.00021762156],"about_ca_topic_score_codex":0.0016011496,"about_ca_topic_score_gemma":0.0034593001,"teacher_disagreement_score":0.00508693,"about_ca_system_score_codex":0.0008266345,"about_ca_system_score_gemma":0.0018226504,"threshold_uncertainty_score":0.017669976},"labels":[],"label_agreement":null},{"id":"W2756408763","doi":"10.2514/6.2017-5308","title":"Spacecraft Component Recognition using a Codebook of Texton Images","year":2017,"lang":"en","type":"article","venue":"AIAA SPACE and Astronautics Forum and Exposition","topic":"Image Processing and 3D Reconstruction","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Neptec Design Group (Canada); Carleton University","funders":"","keywords":"Codebook; Computer science; Component (thermodynamics); Artificial intelligence; Pattern recognition (psychology); Speech recognition; Physics","score_opus":0.01745222654654331,"score_gpt":0.2522090766716704,"score_spread":0.23475685012512712,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2756408763","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":[0.065082684,0.00062497804,0.9213709,0.00022843064,0.00045976127,0.00021328576,0.0021100133,0.0035444836,0.0063653784],"genre_scores_gemma":[0.49950036,0.00085951114,0.46755043,0.00024556834,0.00019530253,0.00022838048,0.009320947,0.00045361224,0.021645846],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99977607,0.000019164581,0.000011967022,0.000069820635,0.00008377174,0.000039216062],"domain_scores_gemma":[0.9996846,0.00003917061,0.00001802122,0.00007555194,0.00015701765,0.000025659429],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018241043,0.00071347435,0.000601103,0.0011675268,0.00045438303,0.0007706731,0.0007565125,0.000721274,0.0048491703],"category_scores_gemma":[0.0010572684,0.00024034684,0.00047681533,0.00165894,0.00027075293,0.0006749327,0.00060347555,0.00070219685,0.0027142225],"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":[0.0009661172,0.00017278895,0.0018468632,0.0001874451,0.000054816588,0.0002360549,0.00007966758,0.032809667,0.113188475,0.005921446,0.019291507,0.82524526],"study_design_scores_gemma":[0.00007770243,0.0002454392,0.005587692,0.000049471237,0.00006820133,0.00049270916,0.00015216852,0.8703656,0.09677044,0.0053481394,0.02078578,0.000056712346],"about_ca_topic_score_codex":0.008482476,"about_ca_topic_score_gemma":0.012863372,"teacher_disagreement_score":0.008482476,"about_ca_system_score_codex":0.00042457404,"about_ca_system_score_gemma":0.0010305346,"threshold_uncertainty_score":0.016866207},"labels":[],"label_agreement":null}]}