{"id":"W6888801866","doi":"10.22008/fk2/wp1tr3/j56zu6","title":"w50acbw7.rtl","year":2022,"lang":"ru","type":"dataset","venue":"Geological Survey of Denmark and Greenland (GEUS)","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Apotex Pharmachem (Canada)","funders":"","keywords":"Process (computing); Identification (biology); Product (mathematics)","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0009443671,0.002504764,0.001968596,0.004883853,0.0007364546,0.003033106,0.003144311,0.002200833,0.2342114],"category_scores_gemma":[0.005411831,0.001191569,0.001160105,0.01086261,0.0004470187,0.001650829,0.001901037,0.001707909,0.2924821],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00111007,"about_ca_system_score_gemma":0.002083238,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04282363,"about_ca_topic_score_gemma":0.06141677,"domain_scores_codex":[0.9990253,0.0001722024,0.0001040803,0.0002972015,0.0001933536,0.0002078118],"domain_scores_gemma":[0.9981191,0.0005188987,0.0001701534,0.0004822315,0.0005264226,0.0001832281],"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":[0.0000219494,0.000005655769,0.0001925646,0.0002880308,0.00001467385,0.000006145277,0.00001154779,0.0001461881,0.00003194938,0.0002867353,0.9981838,0.0008107602],"study_design_scores_gemma":[0.0001908392,0.000009732449,0.001786865,0.0001955022,0.00002415367,0.00002029644,0.00006286334,0.0002906081,0.000155022,0.001146993,0.9960946,0.0000224952],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00002752923,0.00001747498,0.00003348485,0.00002010769,0.000008643346,0.00000284654,0.9992632,0.000197446,0.0004292857],"genre_scores_gemma":[0.0001606846,0.000027073,0.0001360738,0.0000194864,0.000004039761,0.0000344328,0.9988123,0.0001479311,0.0006579129],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.7657886,"threshold_uncertainty_score":0.7835152,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04411541014490554,"score_gpt":0.2757355965138515,"score_spread":0.2316201863689459,"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."}}