{"id":"W7017154468","doi":"","title":"ARCHIVEIT-1830-WEEKLY-XFGLFF-20120410183059-00000-crawling109.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":[0.0009673827,0.002543144,0.001235261,0.007786376,0.002004213,0.005476908,0.002334865,0.001581013,0.7233846],"category_scores_gemma":[0.007709078,0.001796176,0.0008956366,0.009518138,0.0005979714,0.003443647,0.003529934,0.001297821,0.8477956],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002521069,"about_ca_system_score_gemma":0.00243102,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.079994,"about_ca_topic_score_gemma":0.0974505,"domain_scores_codex":[0.9991336,0.00005898357,0.00004792285,0.0001766197,0.0004153721,0.0001675135],"domain_scores_gemma":[0.9945545,0.0005736402,0.0001858902,0.001583936,0.002284723,0.0008172524],"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":[0.0000235821,0.00001143189,0.0001623849,0.00008707916,0.000004024268,0.000007566863,0.00003601242,0.00003275168,0.0001223306,0.0003355911,0.987561,0.01161618],"study_design_scores_gemma":[0.00002896172,0.000007659966,0.001511869,0.00006568355,0.000005040709,0.00003037487,0.00004180746,0.0001627551,0.0007368352,0.00036109,0.9970251,0.00002278649],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"other","genre_scores_codex":[0.0006829112,0.0002712082,0.00272369,0.0004172091,0.0002239842,0.0001906911,0.5860218,0.1504588,0.2590097],"genre_scores_gemma":[0.002759925,0.000412698,0.004475294,0.0003293334,0.00009645538,0.0002042343,0.5773253,0.08866176,0.3257349],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.2766154,"threshold_uncertainty_score":0.3945583,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008135019617373103,"score_gpt":0.1974744496362794,"score_spread":0.1893394300189063,"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."}}