{"id":"W7004932042","doi":"","title":"Ottawa 67's Jack Matier","year":2022,"lang":"en","type":"other","venue":"Bulletin of Miscellaneous Information (Royal Gardens Kew)","topic":"Marine Biology and Environmental Chemistry","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Selection (genetic algorithm); Government (linguistics); Work (physics)","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":[],"category_scores_codex":[0.0003203722,0.0008068556,0.0003542588,0.0008183155,0.006144798,0.002756417,0.0007328751,0.001543987,0.4269067],"category_scores_gemma":[0.0009506796,0.0005441544,0.0003784732,0.000871555,0.000654584,0.001227101,0.001809747,0.001586056,0.1990255],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004933123,"about_ca_system_score_gemma":0.01085225,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.7487615,"about_ca_topic_score_gemma":0.952197,"domain_scores_codex":[0.9995164,0.0000225439,0.000009851125,0.00006549538,0.000198816,0.0001868478],"domain_scores_gemma":[0.9990848,0.00002855309,0.00001461209,0.00002924348,0.0004705924,0.0003721677],"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":[0.000008389513,0.000004948241,0.00009458106,0.00001294705,5.910924e-7,0.00002460705,0.00005671653,0.00001141009,0.00006087348,0.0004394143,0.9918736,0.007411904],"study_design_scores_gemma":[0.000001567432,0.000003493999,0.0005501802,0.00002659937,0.000001132761,0.00001718839,0.0002587574,0.000008766472,0.00004212685,0.00004543531,0.9990402,0.00000452076],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.001346131,0.002591152,0.0002726222,0.008177158,0.004077919,0.00008855417,0.002452855,0.0005056573,0.9804879],"genre_scores_gemma":[0.001095086,0.0004096839,0.000063195,0.0006486921,0.00003133082,0.000005965665,0.0002350627,0.00006214919,0.9974489],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.7487615,"threshold_uncertainty_score":0.817448,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.002820210778421145,"score_gpt":0.1470069013454355,"score_spread":0.1441866905670144,"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."}}