{"id":"W3185298051","doi":"10.17504/protocols.io.bnjgmcjw","title":"Manual Tracing Study: Tibetan Knot v1","year":2020,"lang":"en","type":"preprint","venue":"","topic":"Image Processing and 3D Reconstruction","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Tracing; Prime (order theory); Knot (papermaking); Computer science; Mathematics; Combinatorics; Programming language; Engineering","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":[0.001990558,0.0008062192,0.0006420501,0.001500036,0.001424168,0.0006689905,0.00106019,0.0007404255,0.05416522],"category_scores_gemma":[0.002476098,0.0005608099,0.0003771776,0.001135302,0.0005133323,0.0004055734,0.0006303822,0.000838658,0.01332193],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003219352,"about_ca_system_score_gemma":0.001014839,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003275216,"about_ca_topic_score_gemma":0.004193533,"domain_scores_codex":[0.9993131,0.00009923791,0.00007724994,0.0002286224,0.0001870887,0.00009482967],"domain_scores_gemma":[0.9981279,0.0002596938,0.0001126882,0.0006803593,0.0006288,0.0001905123],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.004208609,0.0009533534,0.02082999,0.00128695,0.00007000312,0.001418703,0.002574836,0.001383902,0.6409945,0.004177491,0.05710159,0.265],"study_design_scores_gemma":[0.0009328793,0.005094983,0.1664962,0.0005137314,0.0002953289,0.005299521,0.001038309,0.01485706,0.4373165,0.004449898,0.3633399,0.0003657728],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4193025,0.001005925,0.4382406,0.0003901203,0.0007676136,0.009372277,0.0365727,0.03285741,0.06149096],"genre_scores_gemma":[0.4113285,0.0008966697,0.4259893,0.0007692697,0.0002261019,0.01720778,0.04661729,0.00997135,0.08699384],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.05416522,"threshold_uncertainty_score":0.1812007,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03186326019132994,"score_gpt":0.2917194839487862,"score_spread":0.2598562237574562,"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."}}