{"id":"W2750018047","doi":"","title":"Annotation-based enrichment of Digital Objects using open-source frameworks","year":2017,"lang":"en","type":"article","venue":"TSpace (University of Toronto)","topic":"Image Processing and 3D Reconstruction","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Simon Fraser University","keywords":"Open source; Annotation; Computer science; Computational biology; Biology; Artificial intelligence; Programming language; Software","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":[],"consensus_categories":[],"category_scores_codex":[0.00009274398,0.00007208628,0.00014543,0.00002742411,0.0004237425,0.0002223767,0.00108657,0.00008265423,0.0001249822],"category_scores_gemma":[0.00003264731,0.00008743205,0.00004971727,0.00003486168,0.0001906682,0.002378904,0.0003493413,0.00007925704,0.000002224548],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008223165,"about_ca_system_score_gemma":0.0001668384,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01282912,"about_ca_topic_score_gemma":0.000648399,"domain_scores_codex":[0.9994601,0.00001789476,0.00006360437,0.0001913885,0.0001519246,0.0001150653],"domain_scores_gemma":[0.9989672,0.00002879927,0.0003518355,0.0004623819,0.0001418558,0.00004795819],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00007457795,0.000196409,0.009444353,0.0001077367,0.00006505274,0.00001249706,0.01407285,0.001636901,0.002292221,0.00167904,0.0001377009,0.9702806],"study_design_scores_gemma":[0.003405759,0.0003830541,0.1462843,0.0006035673,0.00008910385,0.00002123867,0.01229193,0.8284725,0.006242754,0.0008854865,0.0005598087,0.0007604797],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1448376,0.00008601016,0.8353325,0.0004119424,0.0002003959,0.00008929468,0.000002500637,0.00003477462,0.01900499],"genre_scores_gemma":[0.9068381,0.000004078786,0.09256471,0.000009617449,0.00001121217,4.629843e-8,9.478252e-7,0.00000308381,0.000568273],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9695202,"threshold_uncertainty_score":0.9937446,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01903607831923463,"score_gpt":0.2639703244792492,"score_spread":0.2449342461600146,"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."}}