{"id":"W4393656717","doi":"10.5281/zenodo.2598762","title":"A time-course analysis using Differential Static Light Scattering (DSLS) of purified HTT1-3144 Q23 - 2019/01/28","year":2019,"lang":"en","type":"dataset","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Machine Learning in Materials Science","field":"Materials Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Physics; Course (navigation); Differential (mechanical device); Nuclear physics; Astronomy","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":[0.001043205,0.001510628,0.0008838661,0.001492684,0.0006890948,0.0009419615,0.001228329,0.001402554,0.006063465],"category_scores_gemma":[0.001384898,0.0002694378,0.001330092,0.001792377,0.0003368454,0.0004218615,0.0006620586,0.00115416,0.009264017],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001306731,"about_ca_system_score_gemma":0.001187846,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01410281,"about_ca_topic_score_gemma":0.02596286,"domain_scores_codex":[0.9994251,0.00007048167,0.00005106899,0.0002156389,0.0001461778,0.00009150812],"domain_scores_gemma":[0.9992955,0.0001865246,0.00008651744,0.0001667106,0.000204608,0.00006015339],"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":[0.002282884,0.000884162,0.03190512,0.004004995,0.0007961473,0.0005145603,0.0001164176,0.008417092,0.03105123,0.001603568,0.8747314,0.04369234],"study_design_scores_gemma":[0.000905766,0.0006261546,0.1296623,0.0003697839,0.0004176594,0.0009840926,0.0002985978,0.01443111,0.03593215,0.003199742,0.8129954,0.0001772726],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.01681468,0.0005323601,0.0007455745,0.0002243622,0.00007876905,0.00004618074,0.979115,0.001168975,0.001274069],"genre_scores_gemma":[0.006217595,0.0001396366,0.001228122,0.00005128366,0.000005575936,0.00006733958,0.9912961,0.00006601011,0.0009283735],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.01410281,"threshold_uncertainty_score":0.02804148,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02660114062074277,"score_gpt":0.2792163616715169,"score_spread":0.2526152210507741,"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."}}