{"id":"W6998731741","doi":"","title":"ARCHIVEIT-1830-NONE-ZSKXCS-20120116184914-00000-crawling202.us.archive.org-6680.warc.gz","year":2012,"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":[0.001099489,0.002744299,0.001382809,0.008246308,0.002148939,0.005879477,0.002586869,0.001792239,0.7040486],"category_scores_gemma":[0.009152249,0.001982245,0.0009024973,0.01048044,0.0006813114,0.003755699,0.003995598,0.001346789,0.8525106],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002747792,"about_ca_system_score_gemma":0.002916851,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.08692062,"about_ca_topic_score_gemma":0.1044462,"domain_scores_codex":[0.9989236,0.00007484088,0.00006203639,0.0002164717,0.0005199894,0.0002029894],"domain_scores_gemma":[0.9931296,0.0007832902,0.000231964,0.002028532,0.002847345,0.0009793864],"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":[0.00002601885,0.00001007044,0.0001624289,0.0001034269,0.000004320743,0.000008028855,0.00003921145,0.00003397694,0.0001256964,0.000377767,0.9890842,0.01002477],"study_design_scores_gemma":[0.00002979529,0.000007283033,0.001246659,0.00006605389,0.000004778626,0.00003150289,0.00004540082,0.0001473746,0.0007162718,0.0003747894,0.9973072,0.00002278403],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"other","genre_scores_codex":[0.0005861848,0.0002716794,0.002774166,0.0004158626,0.0002340741,0.0001721178,0.6473096,0.1477969,0.2004394],"genre_scores_gemma":[0.002415489,0.0003899726,0.004287399,0.0003365943,0.00009089581,0.0001914181,0.6744634,0.0870393,0.2307856],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.2959514,"threshold_uncertainty_score":0.4221388,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008165021886140128,"score_gpt":0.1975400907727321,"score_spread":0.189375068886592,"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."}}