{"id":"W2354815035","doi":"10.1117/12.2230236","title":"Toward unified query processing for ISR information needs and collection management","year":2016,"lang":"en","type":"article","venue":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","topic":"Data Quality and Management","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Defence Research and Development Canada","funders":"","keywords":"Computer science; Data collection; Process (computing); Information management; Data science; Information integration; Information retrieval; Database","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.02102408,0.001476343,0.003514485,0.006210779,0.002264546,0.01446257,0.005225085,0.002840601,0.001929429],"category_scores_gemma":[0.02509319,0.001247341,0.002518201,0.008105149,0.002198426,0.01621035,0.007226702,0.003138703,0.001422125],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002999086,"about_ca_system_score_gemma":0.00618382,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009973008,"about_ca_topic_score_gemma":0.01112459,"domain_scores_codex":[0.9757947,0.00703239,0.003428967,0.002679393,0.009769659,0.001294928],"domain_scores_gemma":[0.9866752,0.003234722,0.001156071,0.003788563,0.004628463,0.0005169625],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0004672451,0.0008678954,0.007679847,0.001060494,0.0004692837,0.0009705731,0.005214701,0.09932145,0.02741706,0.4284576,0.03421301,0.3938609],"study_design_scores_gemma":[0.00006110884,0.0001563014,0.001367346,0.0002031807,0.0001919287,0.0003690273,0.002959241,0.8100621,0.01232485,0.1280992,0.04404965,0.0001561102],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.005566604,0.000619529,0.9855439,0.001981888,0.00005312798,0.0004446559,0.0003499176,0.001992102,0.003448302],"genre_scores_gemma":[0.1328864,0.0009302818,0.8612186,0.0005872265,0.0002005026,0.0004198338,0.001554567,0.0003883958,0.001814133],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02102408,"threshold_uncertainty_score":0.1111873,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04003776443304195,"score_gpt":0.2894085166195564,"score_spread":0.2493707521865144,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}