{"id":"W6889280807","doi":"10.25592/dgs.corpus-2.0-type-86455","title":"Tokenliste für das Type TORONTO1^","year":2019,"lang":"en","type":"dataset","venue":"Universität Hamburg","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Akademie der Wissenschaften in Hamburg","keywords":"Type (biology); Term (time); Terminal (telecommunication); Sequence (biology)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0009916187,0.00328002,0.00169449,0.005140116,0.001541596,0.002267456,0.002169102,0.002117795,0.1665561],"category_scores_gemma":[0.004206077,0.001271646,0.001219899,0.006864311,0.0007132887,0.002278923,0.002549811,0.002136048,0.221199],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002524724,"about_ca_system_score_gemma":0.004366301,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05494164,"about_ca_topic_score_gemma":0.1094266,"domain_scores_codex":[0.9984488,0.0002400104,0.0002050337,0.0005490308,0.0003060111,0.0002509484],"domain_scores_gemma":[0.9976861,0.0006907705,0.0001652209,0.0005457346,0.0006855043,0.000226579],"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":[0.00007218945,0.000009949387,0.0002198227,0.0003964665,0.00001242993,0.00002461536,0.00003453746,0.0001193205,0.0002248936,0.000349234,0.9964854,0.002051093],"study_design_scores_gemma":[0.0002572981,0.00001974743,0.003218292,0.0001364427,0.0000308901,0.0001319454,0.0001607263,0.0005523352,0.001278205,0.001062789,0.9930964,0.00005485402],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001892549,0.0000535199,0.0002061259,0.00004399354,0.00004866819,0.00001142516,0.9973617,0.001068766,0.001016543],"genre_scores_gemma":[0.0004972004,0.000031797,0.0004186631,0.00002542383,0.00001024162,0.00006329653,0.9974292,0.0003435171,0.001180623],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1665561,"threshold_uncertainty_score":0.5571858,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02399164582062321,"score_gpt":0.3059059163691413,"score_spread":0.2819142705485181,"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."}}