{"id":"W7062390143","doi":"","title":"Stock - Canadian Geese and Goslings","year":2005,"lang":"en","type":"other","venue":"Bulletin of Miscellaneous Information (Royal Gardens Kew)","topic":"Magnetic confinement fusion research","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Stock (firearms); Production (economics); Production model; Stock exchange","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":[0.0002379282,0.001058865,0.000380128,0.0008850514,0.003358621,0.00162375,0.0007991635,0.000747962,0.5138284],"category_scores_gemma":[0.0003900805,0.0003074797,0.000250467,0.001046356,0.0004636825,0.0006548327,0.001299996,0.000762586,0.1973825],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002792708,"about_ca_system_score_gemma":0.00365532,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.6720067,"about_ca_topic_score_gemma":0.9288468,"domain_scores_codex":[0.9998022,0.000005909646,0.000003263554,0.00003838183,0.0001007375,0.0000496398],"domain_scores_gemma":[0.9994953,0.00001260383,0.000012113,0.00002366373,0.0002090281,0.0002473036],"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":[0.000052354,0.00002900326,0.001156119,0.00005791082,0.000002990947,0.00008646512,0.0001429026,0.00002626531,0.0009243437,0.0009364104,0.9022062,0.094379],"study_design_scores_gemma":[0.00000482511,0.00001394324,0.005358789,0.00003156706,0.000002945851,0.00005232932,0.0003268264,0.00003138336,0.0003549753,0.0001194761,0.9936947,0.000008267859],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"dataset","genre_scores_codex":[0.004506885,0.002030795,0.000779532,0.002135446,0.0009076935,0.0001139111,0.01614144,0.001318839,0.9720656],"genre_scores_gemma":[0.004542577,0.000613171,0.0004763941,0.0002057866,0.00003161615,0.00001438324,0.002325383,0.0001255064,0.9916652],"genre_candidate":"dataset","genre_consensus":null,"teacher_disagreement_score":0.5138284,"threshold_uncertainty_score":0.6934648,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004564704121125007,"score_gpt":0.1890924771475093,"score_spread":0.1845277730263843,"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."}}