{"id":"W7026614148","doi":"","title":"ARCHIVEIT-1830-NONE-LPSLZD-20110805192400-00000-crawling203.us.archive.org-6683.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":"Identification (biology); Work (physics); Process (computing)","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":[0.001096043,0.002753287,0.001389299,0.007947417,0.002153861,0.005956773,0.002606116,0.001912442,0.7155259],"category_scores_gemma":[0.008934256,0.00201825,0.0009266257,0.009943744,0.0006821524,0.003753712,0.004043334,0.001436627,0.8626679],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002847912,"about_ca_system_score_gemma":0.002749757,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.08206701,"about_ca_topic_score_gemma":0.09456649,"domain_scores_codex":[0.9989641,0.00007994233,0.0000608175,0.0001984336,0.0004962088,0.0002005043],"domain_scores_gemma":[0.9934116,0.0007830492,0.000221312,0.001984653,0.002665388,0.0009340299],"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":[0.00002750865,0.00001203016,0.0001533903,0.0000983283,0.000004134295,0.000008048219,0.0000361473,0.00003714247,0.0001270231,0.0003751335,0.9886824,0.01043879],"study_design_scores_gemma":[0.00003119799,0.000007904556,0.001187888,0.00006345111,0.000004417723,0.00003087247,0.00004238756,0.0001663552,0.0007379241,0.0003618252,0.9973423,0.00002350207],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"other","genre_scores_codex":[0.0005953495,0.0002470471,0.002807586,0.0004425879,0.0002424675,0.0001891347,0.6275663,0.1468207,0.2210888],"genre_scores_gemma":[0.002470649,0.0003714983,0.00435578,0.000347903,0.0000926869,0.0002049803,0.6414586,0.08723906,0.2634588],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.2844741,"threshold_uncertainty_score":0.4057677,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009584944910995902,"score_gpt":0.1932264132324352,"score_spread":0.1836414683214393,"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."}}