{"id":"W6989395874","doi":"","title":"ARCHIVEIT-279-WEEKLY-DBWWRE-20110913135339-00000-crawling212.us.archive.org-6680.warc.gz","year":2011,"lang":"en","type":"other","venue":"Bulletin of Miscellaneous Information (Royal Gardens Kew)","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Process (computing); Work (physics); Identification (biology); Product (mathematics)","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":[0.001087396,0.002556349,0.001286051,0.006548028,0.002138199,0.005956448,0.002552476,0.001922347,0.8111034],"category_scores_gemma":[0.008000057,0.002189424,0.0009492759,0.008342896,0.0006419986,0.004200598,0.004194377,0.001490013,0.9067786],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002716951,"about_ca_system_score_gemma":0.002005536,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04960341,"about_ca_topic_score_gemma":0.06424209,"domain_scores_codex":[0.9991022,0.0000804349,0.00006226302,0.0001797789,0.000408317,0.0001670456],"domain_scores_gemma":[0.9942135,0.0006762134,0.0002226742,0.00199028,0.001984312,0.00091306],"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":[0.00002206449,0.00001162611,0.0001330504,0.00007409383,0.000003318847,0.00000722934,0.00003470153,0.00002783133,0.0001057607,0.0003639128,0.989228,0.009988508],"study_design_scores_gemma":[0.00002789894,0.000006850446,0.001105134,0.00005025111,0.000003873176,0.00002856608,0.00003825295,0.0001411332,0.0006632144,0.0002569807,0.9976583,0.00001952726],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"other","genre_scores_codex":[0.0006333567,0.0002166843,0.003092489,0.0005337413,0.0002420883,0.0002125564,0.532564,0.1392908,0.3232142],"genre_scores_gemma":[0.00308684,0.0003979323,0.00395056,0.0003854854,0.0001188311,0.0002549139,0.4535653,0.09302386,0.4452163],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.1888966,"threshold_uncertainty_score":0.2694381,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009378153837644993,"score_gpt":0.1921720980417131,"score_spread":0.1827939442040681,"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."}}