{"id":"W4393512370","doi":"10.5281/zenodo.3575254","title":"Custom young-old population MNI-space MRI anatomical template","year":2019,"lang":"en","type":"dataset","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Advanced MRI Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University; McGill University; Montreal Neurological Institute and Hospital","funders":"","keywords":"Space (punctuation); Population; Computer science; Computer graphics (images); Geography; Geology; Artificial intelligence; Cartography; Medicine","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":[0.0009840399,0.001873172,0.001091228,0.001811996,0.0006297961,0.001099551,0.002714495,0.001432329,0.04151112],"category_scores_gemma":[0.003406721,0.0005408754,0.000983618,0.002188486,0.0003121202,0.0008680074,0.001395672,0.001014176,0.06150329],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008749345,"about_ca_system_score_gemma":0.001558279,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01227516,"about_ca_topic_score_gemma":0.04212836,"domain_scores_codex":[0.999545,0.00006441704,0.00006181081,0.0002270197,0.00005440721,0.00004718873],"domain_scores_gemma":[0.9992867,0.0001098947,0.00006411996,0.0002416525,0.0002390076,0.00005865948],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0004863871,0.0001100591,0.004740683,0.0008074728,0.0001902481,0.0002893792,0.0001144044,0.0005321137,0.001431179,0.0007950876,0.9692786,0.02122445],"study_design_scores_gemma":[0.0008086562,0.0001077975,0.0375602,0.0004018628,0.0003556827,0.002319524,0.0002632563,0.002174455,0.002312039,0.004375335,0.9492217,0.00009951343],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00529799,0.000307758,0.002928087,0.0000977302,0.00007415271,0.0002482629,0.9860443,0.001979918,0.003021787],"genre_scores_gemma":[0.003755696,0.0000783251,0.002446977,0.00007192364,0.00001298348,0.0005944918,0.9907779,0.0001765663,0.002085239],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.04151112,"threshold_uncertainty_score":0.1388685,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0359296966654982,"score_gpt":0.3108628218744721,"score_spread":0.2749331252089739,"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."}}