{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts","scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0006530364,0.0003048824,0.0002496603,0.0006699384,0.003108255,0.00139684,0.001527245,0.0002593305,0.006475313],"category_scores_gemma":[0.003140973,0.0003351033,0.0001069588,0.001695712,0.0002188682,0.0002690227,0.001022991,0.0007882078,0.1645323],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003413723,"about_ca_system_score_gemma":0.000007530392,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004539581,"about_ca_topic_score_gemma":0.000002301243,"domain_scores_codex":[0.9965477,0.0008151424,0.0004568957,0.0009460961,0.0007245936,0.0005095619],"domain_scores_gemma":[0.9981342,0.00009080399,0.0003175497,0.0009818999,0.0003013483,0.0001742181],"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":[0.00004154891,0.00008598696,1.235629e-8,0.0001145505,0.0000123144,0.0000294508,0.00003945412,0.00001303455,0.0256745,0.00007696563,0.9524978,0.02141443],"study_design_scores_gemma":[0.0003504188,0.0001628644,0.0000715463,0.00004329653,0.00002324323,0.0002761121,0.00005634843,0.001195123,0.004999068,0.00005236582,0.9924224,0.0003472374],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0005938084,0.00001142413,0.0003011417,0.0004983941,0.0009638472,0.0008834826,0.9822336,0.009511906,0.005002334],"genre_scores_gemma":[0.007461633,0.0002381259,0.00001231868,0.0003953098,0.0003353408,3.91343e-7,0.9876516,0.002100913,0.00180433],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.158057,"threshold_uncertainty_score":0.9999101,"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."}}