{"id":"W2885601112","doi":"10.71781/9780","title":"Feedforward deep architectures for classification and synthesis","year":2017,"lang":"en","type":"dissertation","venue":"Open MIND","topic":"Embedded Systems Design Techniques","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Samsung; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs; Canadian Institute for Advanced Research","keywords":"Feed forward; Computer science; Artificial intelligence; Neuroscience; Psychology; Engineering; Control engineering","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006757987,0.0008194923,0.000568279,0.0006046633,0.0003450173,0.001208502,0.0009131291,0.0009905819,0.007372369],"category_scores_gemma":[0.001783142,0.0004261849,0.0007798746,0.0006584979,0.0005180563,0.001525812,0.0009411998,0.001513523,0.001835587],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000960988,"about_ca_system_score_gemma":0.0009760835,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00488765,"about_ca_topic_score_gemma":0.007861246,"domain_scores_codex":[0.9997038,0.00005801422,0.00002522368,0.00008267586,0.00008772459,0.00004247099],"domain_scores_gemma":[0.9995983,0.0001884389,0.00002858772,0.00007636518,0.00008814233,0.00002008836],"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":[0.0001839324,0.00005276274,0.000470106,0.0003051509,0.00007541073,0.00009702119,0.0001420374,0.2429684,0.02966873,0.04859054,0.006653385,0.6707926],"study_design_scores_gemma":[0.00001499872,0.00005612397,0.0003532045,0.00005613109,0.00002315721,0.0000434811,0.00002662533,0.9433545,0.0112214,0.03138568,0.01344747,0.00001725029],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.008812607,0.002275319,0.980891,0.0003971666,0.0001842295,0.00003674596,0.0002206739,0.001947838,0.005234479],"genre_scores_gemma":[0.4054658,0.00453723,0.5574811,0.0003411637,0.0002752562,0.0002239725,0.001164344,0.0004242552,0.03008694],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007372369,"threshold_uncertainty_score":0.02466309,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.067033785367864,"score_gpt":0.3605821187667033,"score_spread":0.2935483333988393,"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."}}