{"id":"W6935988783","doi":"10.57907/mirri/0tk4uu","title":"MIRRI0029286","year":2022,"lang":"en","type":"dataset","venue":"Entrepôt pour orphelin","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Organism; Taxon; Identification (biology); Point (geometry)","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0008856826,0.0009455637,0.0008627574,0.0006366841,0.0003239137,0.0001595573,0.001828272,0.0004706189,0.9991596],"category_scores_gemma":[0.0006141901,0.001012174,0.0005288752,0.0006041495,0.0001087021,0.0001246809,0.001203439,0.001890064,0.9852656],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007891985,"about_ca_system_score_gemma":0.0006493418,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001241336,"about_ca_topic_score_gemma":0.0003975141,"domain_scores_codex":[0.9944509,0.0006719732,0.0009141833,0.001354216,0.001523429,0.001085277],"domain_scores_gemma":[0.9958954,0.0003348748,0.0007679178,0.002493809,0.0001172315,0.0003907106],"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":[0.00008670936,0.0004967633,0.00002038601,0.00008794025,0.0002221278,0.0008656649,0.00003134154,0.00004889456,0.0001462181,0.00001418462,0.9977605,0.0002192712],"study_design_scores_gemma":[0.0009982858,0.00006168878,0.00001679579,0.00004956599,0.0003225261,0.0001257309,0.00009324126,0.000008363892,0.00009305809,0.0001308249,0.9970667,0.001033225],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00007543745,0.001384451,0.000002315219,0.0004072056,0.001960408,0.0006212013,0.9950333,0.0004764414,0.00003923959],"genre_scores_gemma":[0.000003476202,0.0002408223,0.0001797481,0.000784213,0.001019218,0.0002406527,0.9885406,0.0003080493,0.008683204],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.01389397,"threshold_uncertainty_score":0.9992329,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0172844641368919,"score_gpt":0.2672980167507813,"score_spread":0.2500135526138894,"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."}}