{"id":"W6989430573","doi":"","title":"ARCHIVEIT-3490-PATCH-EHOUPA-20130129182023-00000-crawling113.us.archive.org-6682.warc.gz","year":2013,"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); 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":[0.00105642,0.002446231,0.001599094,0.006466758,0.002025826,0.006007512,0.003094334,0.001953294,0.8492595],"category_scores_gemma":[0.01045813,0.002214358,0.001179818,0.00845255,0.000684951,0.00488888,0.005028672,0.001546999,0.9317248],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002227287,"about_ca_system_score_gemma":0.001923188,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03553486,"about_ca_topic_score_gemma":0.03684309,"domain_scores_codex":[0.9990883,0.00008636283,0.00005909508,0.0002165611,0.0003818594,0.000167899],"domain_scores_gemma":[0.9927976,0.001020601,0.0002331923,0.002519464,0.002522965,0.000906241],"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":[0.00002502557,0.00001008054,0.0001110005,0.00008721631,0.000003598323,0.000007025771,0.00003907577,0.00002592558,0.00008078446,0.0003114817,0.9883697,0.01092897],"study_design_scores_gemma":[0.00002941529,0.000006276558,0.0007623452,0.00007093194,0.000004094944,0.00003034293,0.00004185639,0.0001152575,0.0005117063,0.000402013,0.9980054,0.0000201843],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"other","genre_scores_codex":[0.0005268977,0.0002426976,0.004372802,0.0005091673,0.000289693,0.000202477,0.4663044,0.2184433,0.3091087],"genre_scores_gemma":[0.003126773,0.00043551,0.005812987,0.0004991197,0.0001236142,0.0002991059,0.425987,0.2027441,0.3609718],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.1507405,"threshold_uncertainty_score":0.215013,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006902192132319337,"score_gpt":0.1923557266713293,"score_spread":0.1854535345390099,"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."}}