{"id":"W1910577028","doi":"10.1109/cmpcmm.1993.659092","title":"The OSIRIS ATM Interface: Experience and Insights","year":2005,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Bell (Canada)","funders":"","keywords":"Osiris; Interface (matter); Computer science; Human–computer interaction; Operating system","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":[0.01651268,0.0008961965,0.0006158618,0.0009528879,0.0006614298,0.004798645,0.003449492,0.001760634,0.007136576],"category_scores_gemma":[0.0156402,0.0003762091,0.0003550769,0.001369859,0.001555535,0.006600047,0.0015719,0.002788515,0.001728735],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009621154,"about_ca_system_score_gemma":0.001015045,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002989327,"about_ca_topic_score_gemma":0.00351561,"domain_scores_codex":[0.9960406,0.001411122,0.0001631085,0.0003303266,0.001657947,0.0003969013],"domain_scores_gemma":[0.991104,0.004274148,0.0002912936,0.0006018051,0.003010332,0.0007184967],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.003232876,0.002259958,0.03616146,0.001145178,0.0001554823,0.0008605135,0.008874072,0.011927,0.02935219,0.03401189,0.03238119,0.8396381],"study_design_scores_gemma":[0.0008348313,0.01001886,0.03436642,0.001744159,0.0006049311,0.005445136,0.01947437,0.09327894,0.1214952,0.03205194,0.6801033,0.0005819969],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5720759,0.0430829,0.1893098,0.01675609,0.0008269853,0.0003737077,0.0009028122,0.002290104,0.1743818],"genre_scores_gemma":[0.8410492,0.02361682,0.1001119,0.002510676,0.0007636329,0.0001001318,0.001467997,0.0007891101,0.02959058],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01651268,"threshold_uncertainty_score":0.08732843,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009655738437953509,"score_gpt":0.2603533038630014,"score_spread":0.2506975654250478,"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."}}