{"id":"W3164038056","doi":"10.1109/icip42928.2021.9506712","title":"Latent-Space Scalability for Multi-Task Collaborative Intelligence","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Visual Attention and Saliency Detection","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Computer science; Scalability; Task (project management); Object (grammar); Space (punctuation); Artificial intelligence; Function (biology); Object detection; Pixel; Computer vision; Machine learning; Pattern recognition (psychology); Database; Engineering","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005297482,0.0002811444,0.0003474947,0.0001097857,0.0001678872,0.0005892948,0.0008908829,0.0002779632,0.00005342576],"category_scores_gemma":[0.0002412339,0.0002591372,0.0002464768,0.000563933,0.00007160166,0.00030859,0.001216469,0.0003573319,0.00004002335],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001439549,"about_ca_system_score_gemma":0.0003257113,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007681675,"about_ca_topic_score_gemma":0.0002341134,"domain_scores_codex":[0.9976442,0.0001870314,0.0004389368,0.001136703,0.0002957871,0.0002973027],"domain_scores_gemma":[0.9976447,0.00009495024,0.0002008902,0.0009139378,0.001013315,0.000132193],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001747808,0.005400142,0.006418474,0.002281624,0.0008458117,0.00006026984,0.02306966,0.02085789,0.01471644,0.3751769,0.00437856,0.5466195],"study_design_scores_gemma":[0.0002999333,0.0001726355,0.003102711,0.0001080001,0.00002246132,0.000005032956,0.0006240639,0.9562638,0.03204779,0.005101325,0.0015911,0.0006611275],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01126175,0.0001439753,0.9834346,0.001138483,0.002332841,0.0009629959,0.00001614426,0.0003546549,0.0003546056],"genre_scores_gemma":[0.627872,0.00007138784,0.3684716,0.0002696977,0.0000630587,0.0003004188,0.00003470635,0.00001514265,0.002901961],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9354059,"threshold_uncertainty_score":0.9999861,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0669355368758658,"score_gpt":0.354052696838362,"score_spread":0.2871171599624962,"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."}}