{"id":"W4405240087","doi":"10.21105/joss.07399","title":"SlicerSPECTRecon: A 3D Slicer Extension for SPECT Image Reconstruction","year":2024,"lang":"en","type":"article","venue":"The Journal of Open Source Software","topic":"Medical Imaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research","keywords":"Extension (predicate logic); Computer science; Computer graphics (images); Artificial intelligence; Computer vision; Image (mathematics); Programming language","routes":{"ca_aff":true,"ca_fund":true,"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":[],"consensus_categories":[],"category_scores_codex":[0.001136332,0.0001096608,0.0002679433,0.00009371443,0.0001416382,0.0001442601,0.0003386334,0.00004452896,0.0005842508],"category_scores_gemma":[0.0003524964,0.00006401908,0.0001568889,0.0002021098,0.0001115812,0.0002325294,0.00009490398,0.0004061897,0.00002776972],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008710515,"about_ca_system_score_gemma":0.0001535952,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002380512,"about_ca_topic_score_gemma":0.000001235718,"domain_scores_codex":[0.9990839,0.00004368206,0.0003731564,0.0001374359,0.0002049953,0.000156779],"domain_scores_gemma":[0.9988483,0.0003288709,0.0001713057,0.000292697,0.0002307167,0.0001281482],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0006143209,0.0001410744,0.0001544639,0.0002638469,0.0002649216,0.00006964317,0.001432575,0.000009798094,0.02947681,0.0005224287,0.4642662,0.5027839],"study_design_scores_gemma":[0.00248754,0.001316819,0.000569428,0.003617975,0.00163105,0.02760743,0.002704943,0.009226553,0.01813203,0.01234328,0.9199539,0.0004090406],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1301055,0.001976185,0.7961485,0.06600826,0.0006442568,0.002072586,0.00002259835,0.0003431853,0.002678931],"genre_scores_gemma":[0.2336933,0.001104852,0.7522181,0.00286446,0.002578202,0.00007466983,0.00001560713,0.0001475444,0.007303244],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.5023748,"threshold_uncertainty_score":0.6397137,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03526505073734853,"score_gpt":0.3594754118826237,"score_spread":0.3242103611452751,"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."}}