{"id":"W6989334687","doi":"","title":"ARCHIVEIT-1830-NONE-EVZEZR-20111004151823-00001-crawling205.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":"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":[0.001141447,0.002695645,0.001425222,0.007379882,0.002010089,0.005910284,0.002588989,0.00180026,0.7043254],"category_scores_gemma":[0.009137744,0.001935431,0.0008725139,0.009357084,0.0006325379,0.003587894,0.003908804,0.001371089,0.8547509],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002519433,"about_ca_system_score_gemma":0.002553159,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.07166787,"about_ca_topic_score_gemma":0.08538621,"domain_scores_codex":[0.9989428,0.00008291735,0.00006713936,0.0002173432,0.0004949736,0.0001947578],"domain_scores_gemma":[0.9937651,0.0008006808,0.0002187638,0.001958908,0.002459697,0.0007967519],"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":[0.00002969031,0.00001173413,0.0001769586,0.0001097654,0.000005016057,0.000008878681,0.00004073814,0.0000426646,0.0001285661,0.0004217621,0.987812,0.01121211],"study_design_scores_gemma":[0.0000299808,0.000007077679,0.001173323,0.00006620622,0.000004767262,0.00003118509,0.00004502213,0.0001555684,0.0006880364,0.0003942684,0.9973827,0.00002182567],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"other","genre_scores_codex":[0.0006243995,0.0002734763,0.003152506,0.0004289064,0.0002352481,0.0001704829,0.6560348,0.1411973,0.1978828],"genre_scores_gemma":[0.002432202,0.0003914632,0.004693379,0.0003145882,0.00008243886,0.0002031816,0.6743382,0.08564179,0.2319028],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.2956746,"threshold_uncertainty_score":0.4217439,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009525290048372236,"score_gpt":0.1938856578256744,"score_spread":0.1843603677773022,"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."}}