{"id":"W6998786637","doi":"","title":"ARCHIVEIT-2475-MONTHLY-ITRRLT-20111121184832-00042-crawling208.us.archive.org-6682.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":"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":[0.000878676,0.002082752,0.00126773,0.006901648,0.001834062,0.005503997,0.002226726,0.001360024,0.8594375],"category_scores_gemma":[0.006541213,0.001560509,0.0008714205,0.01248235,0.0005263278,0.003025297,0.003089094,0.0013677,0.9246862],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002252207,"about_ca_system_score_gemma":0.002100501,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.06848598,"about_ca_topic_score_gemma":0.07189265,"domain_scores_codex":[0.9992812,0.00006229121,0.00004615738,0.0001363563,0.0003390134,0.0001350573],"domain_scores_gemma":[0.9954357,0.000610303,0.0001944881,0.00118229,0.001896873,0.0006803501],"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":[0.00001672575,0.000007734937,0.0001144197,0.00007661445,0.000002683311,0.000005192437,0.00002701355,0.00002539846,0.0000562788,0.0002829586,0.9884297,0.01095533],"study_design_scores_gemma":[0.00001786227,0.000003608556,0.0009392676,0.00006141701,0.00000318525,0.00001475973,0.00003139645,0.00006877946,0.0002938618,0.0002852806,0.9982666,0.00001392095],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"other","genre_scores_codex":[0.0003426351,0.0001896778,0.001498585,0.0003241267,0.0001667035,0.0001036848,0.6770995,0.04748415,0.2727909],"genre_scores_gemma":[0.002068013,0.0004674975,0.002836769,0.0003188575,0.0001064416,0.000203345,0.5527821,0.04980032,0.3914167],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.1405625,"threshold_uncertainty_score":0.2004953,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008624807665350858,"score_gpt":0.1893871071034257,"score_spread":0.1807622994380748,"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."}}