{"id":"W4393806612","doi":"10.5281/zenodo.10108362","title":"Automated sarcomere detection Matlab tool","year":2023,"lang":"en","type":"dataset","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Brain Tumor Detection and Classification","field":"Neuroscience","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Agence Nationale de la Recherche; Deutsche Forschungsgemeinschaft; Frontiers Foundation; Aix-Marseille Université","keywords":"Sarcomere; MATLAB; Computer science; Computer graphics (images); Artificial intelligence; Biology; Operating system","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":[0.001002675,0.002435853,0.001232366,0.00292572,0.0006374235,0.001562013,0.00224999,0.0009622332,0.03662625],"category_scores_gemma":[0.0019362,0.0007093388,0.001415548,0.001713598,0.0002647611,0.0007380026,0.001418093,0.001327036,0.06610763],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008359319,"about_ca_system_score_gemma":0.001210924,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005597192,"about_ca_topic_score_gemma":0.01420873,"domain_scores_codex":[0.9992914,0.00006696254,0.00007014663,0.0002928005,0.0001884533,0.00009019229],"domain_scores_gemma":[0.9994494,0.0001088023,0.00005307002,0.0001983467,0.0001553845,0.00003505453],"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":[0.0003652525,0.0001210925,0.002257914,0.0008114595,0.0001763703,0.0001259028,0.00005740059,0.00305785,0.01041963,0.001605304,0.909236,0.07176568],"study_design_scores_gemma":[0.0004127792,0.0001335143,0.01252161,0.0002243277,0.0001292755,0.0008621226,0.00007685473,0.06087945,0.04006892,0.007320982,0.8772267,0.0001435263],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"software","genre_scores_codex":[0.007919863,0.0007833213,0.07841477,0.000214901,0.0003064292,0.0003125563,0.7450298,0.1600154,0.007002912],"genre_scores_gemma":[0.008512584,0.0002610635,0.0920326,0.0001923048,0.00003536796,0.001188128,0.8845276,0.005294118,0.007956217],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.03662625,"threshold_uncertainty_score":0.122527,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05709424723810289,"score_gpt":0.2767758276231683,"score_spread":0.2196815803850654,"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."}}