{"id":"W3211547869","doi":"","title":"Big data meet deep data: Characterizing spatial navigation in hippocampal amnesia","year":2021,"lang":"en","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Visual Attention and Saliency Detection","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Baycrest Hospital; York University","funders":"","keywords":"Computer science; Amnesia; Big data; Hippocampal formation; Artificial intelligence; Neuroscience; Data mining; Cognitive psychology; Psychology","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","scholarly_communication","open_science"],"consensus_categories":["open_science"],"category_scores_codex":[0.007454409,0.0003978248,0.0004696548,0.000328098,0.0003271083,0.001654892,0.006793285,0.0003531408,0.00003476915],"category_scores_gemma":[0.001216731,0.0004594716,0.0001129857,0.0008730157,0.000123645,0.001296696,0.01198532,0.0008225023,0.00003216399],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001631757,"about_ca_system_score_gemma":0.0004767431,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002973737,"about_ca_topic_score_gemma":0.01053676,"domain_scores_codex":[0.9911178,0.004711888,0.0008858375,0.002078927,0.0007490307,0.0004565587],"domain_scores_gemma":[0.9890161,0.0004779409,0.0006881293,0.008432248,0.001198747,0.0001868824],"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":[0.00002006684,0.001525464,0.005659644,0.0004789599,0.0001213257,0.00008772691,0.01311913,0.0001220331,0.01515217,0.01846526,0.0004692095,0.944779],"study_design_scores_gemma":[0.0008842723,0.000001023105,0.03449584,0.002823579,0.00004817082,0.00005505654,0.0002415141,0.9372425,0.01563805,0.002154412,0.00541441,0.001001183],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1467284,0.0004082413,0.8431237,0.005765609,0.001625774,0.0003981628,0.00009750981,0.0003056416,0.001546959],"genre_scores_gemma":[0.9381704,0.0002956774,0.05215536,0.0001684781,0.0001201846,0.00004370098,0.008727308,0.00003907533,0.0002798045],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9437778,"threshold_uncertainty_score":0.9997857,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05420562393424952,"score_gpt":0.2775438625599216,"score_spread":0.2233382386256721,"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."}}