{"id":"W6984260182","doi":"","title":"ILODP EP 001","year":2014,"lang":"en","type":"other","venue":"Bulletin of Miscellaneous Information (Royal Gardens Kew)","topic":"Machine Learning in Materials Science","field":"Materials Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Government (linguistics); Legislation; Payment; Legislature","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":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.001237666,0.0005295587,0.0004384888,0.001565248,0.002651569,0.008064765,0.001491942,0.004961908,0.5484057],"category_scores_gemma":[0.004516974,0.0003651571,0.000551283,0.001597613,0.0009425881,0.002041278,0.002478267,0.003892123,0.379954],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004364518,"about_ca_system_score_gemma":0.006464255,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03019373,"about_ca_topic_score_gemma":0.06556073,"domain_scores_codex":[0.9985232,0.00009029752,0.00004763321,0.0001841598,0.0008785389,0.0002762408],"domain_scores_gemma":[0.9983734,0.0002313462,0.00005844039,0.0001896268,0.0007876297,0.0003595162],"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":[0.00002108395,0.00002759275,0.000100584,0.00008895233,0.000001744383,0.0000577135,0.00003274664,0.0000344765,0.0001970191,0.02314565,0.9501239,0.02616856],"study_design_scores_gemma":[0.000002847683,0.000005205472,0.0002448046,0.00002924516,8.340256e-7,0.00001579546,0.00002038011,0.00002007035,0.00008416025,0.0010207,0.9985533,0.000002615365],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.0001845375,0.0003704719,0.0003441235,0.003196861,0.002044698,0.00006540241,0.001959975,0.0002874481,0.9915466],"genre_scores_gemma":[0.0008064305,0.0001859476,0.000167827,0.001979967,0.0002518637,0.00003340445,0.0006860375,0.0001113373,0.9957771],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.4515943,"threshold_uncertainty_score":0.6441444,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004661177687473744,"score_gpt":0.1910014006571873,"score_spread":0.1863402229697136,"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."}}