{"id":"W2997498756","doi":"10.71781/10271","title":"Visual question answering with modules and language modeling","year":2019,"lang":"en","type":"dissertation","venue":"Open MIND","topic":"Multimodal Machine Learning Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Compute Canada; Nvidia","keywords":"Question answering; Computer science; Natural language processing; Linguistics; Artificial intelligence; Information retrieval; Philosophy","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":[0.002066622,0.001019812,0.0007096985,0.001720368,0.0005545919,0.00456033,0.002428367,0.002032563,0.01327386],"category_scores_gemma":[0.008393456,0.0007143868,0.003212552,0.001118857,0.001135582,0.006196272,0.003307073,0.001873139,0.003947178],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00153767,"about_ca_system_score_gemma":0.001181084,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006188188,"about_ca_topic_score_gemma":0.006460973,"domain_scores_codex":[0.9982898,0.0006797457,0.00009963872,0.0005009641,0.0003003445,0.0001295122],"domain_scores_gemma":[0.9979427,0.001153364,0.000116571,0.0004338612,0.0002485252,0.0001048629],"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":[0.0005010372,0.000247833,0.003882907,0.001320238,0.0003829047,0.0005715856,0.002978063,0.1039213,0.02177792,0.2903885,0.01831844,0.5557093],"study_design_scores_gemma":[0.00004524008,0.000107155,0.0009309982,0.0001947379,0.0001082875,0.0004080416,0.0004225354,0.6233263,0.009425167,0.3119248,0.05304013,0.00006670218],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.007627398,0.0007827206,0.9765781,0.0007482204,0.00007203952,0.0001789308,0.0005571884,0.007141822,0.006313715],"genre_scores_gemma":[0.26484,0.001296729,0.7149731,0.0007031138,0.0001364061,0.0005653222,0.00244657,0.00108907,0.01394965],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01327386,"threshold_uncertainty_score":0.04440552,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0147581786918676,"score_gpt":0.3420031289771181,"score_spread":0.3272449502852505,"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."}}