{"id":"W6980011005","doi":"","title":"ARCHIVEIT-279-MONTHLY-CGZRBU-20130128072139-00000-crawling114.us.archive.org-6680.warc.gz","year":2013,"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); Work (physics); 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":[0.001238998,0.002479738,0.00129883,0.007110049,0.002095842,0.00608138,0.002450075,0.001644839,0.7758374],"category_scores_gemma":[0.009935204,0.002079159,0.0009208912,0.00982741,0.0006505747,0.004237291,0.004138161,0.001412011,0.8777675],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002900273,"about_ca_system_score_gemma":0.002280818,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.06288458,"about_ca_topic_score_gemma":0.07841608,"domain_scores_codex":[0.9989811,0.00008656563,0.00006852871,0.0002062765,0.0004752214,0.0001823649],"domain_scores_gemma":[0.9931774,0.0007946717,0.0002894105,0.002268988,0.002432983,0.001036475],"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":[0.00002449753,0.000009690686,0.0001706856,0.00007762814,0.000003851906,0.000006386481,0.00003620408,0.0000275909,0.00008574937,0.0003609751,0.9902456,0.008951067],"study_design_scores_gemma":[0.00003473726,0.00000719872,0.001636331,0.00005852242,0.000004999702,0.00002682008,0.00004190753,0.0001595884,0.0007156913,0.0003246253,0.996967,0.00002264285],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"other","genre_scores_codex":[0.0006086612,0.0002050966,0.002703025,0.0004691793,0.0002111007,0.0001765822,0.6209139,0.1414585,0.2332541],"genre_scores_gemma":[0.003582574,0.0004153817,0.004300237,0.0003851877,0.0001364647,0.0002704477,0.5614364,0.1166527,0.3128207],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.2241626,"threshold_uncertainty_score":0.3197407,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006302210832460481,"score_gpt":0.1884877653440793,"score_spread":0.1821855545116188,"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."}}