{"id":"W4393508128","doi":"10.5281/zenodo.7779045","title":"Data Supplement: GIRFReco.jl: An Open-Source Pipeline for Spiral Magnetic Resonance Image (MRI) Reconstruction in Julia","year":2023,"lang":"en","type":"dataset","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Geological and Geophysical Studies","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; University of British Columbia; University Health Network","funders":"","keywords":"Magnetic resonance imaging; Spiral (railway); Pipeline (software); Nuclear magnetic resonance; Open source; Physics; Computer science; Engineering; Medicine; Radiology","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":[0.001060818,0.002888843,0.001771441,0.002455479,0.0008994113,0.002432377,0.00360895,0.002356949,0.2459236],"category_scores_gemma":[0.006167147,0.0009141023,0.001567107,0.003335804,0.0004882595,0.001360124,0.002526359,0.001789598,0.2554962],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001515325,"about_ca_system_score_gemma":0.00246107,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01903527,"about_ca_topic_score_gemma":0.04866129,"domain_scores_codex":[0.9992688,0.0001038726,0.00008829757,0.0002275207,0.000178756,0.0001326548],"domain_scores_gemma":[0.9973827,0.0006678306,0.0002039005,0.0006944414,0.0007720641,0.0002789439],"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":[0.00004096517,0.00001145573,0.0001947033,0.0002841044,0.00001481007,0.00001391468,0.0000073956,0.0001283542,0.0001047342,0.000143634,0.9977838,0.001272138],"study_design_scores_gemma":[0.0004257126,0.0000260301,0.003218088,0.0003304472,0.00004003308,0.0001547381,0.00004635083,0.0007104538,0.0007893046,0.002436237,0.991771,0.00005179697],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00008153223,0.00004181518,0.0001785029,0.00006725796,0.00004159718,0.00001582549,0.9976754,0.00130664,0.0005913784],"genre_scores_gemma":[0.000299906,0.00003215002,0.0005040208,0.00005969285,0.00001197437,0.00008506572,0.998027,0.0003697579,0.0006103772],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.2459236,"threshold_uncertainty_score":0.8226965,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06503201123370259,"score_gpt":0.2674519618705175,"score_spread":0.2024199506368149,"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."}}