{"id":"W6917569302","doi":"10.57760/sciencedb.01957","title":"Data of 2ELRP in an EC with possible failed home deliveries","year":2022,"lang":"en","type":"dataset","venue":"ScienceDB","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Wilfrid Laurier University","funders":"","keywords":"Data collection; Work (physics); Government (linguistics); Population","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":[],"consensus_categories":[],"category_scores_codex":[0.0008036052,0.002214524,0.00118313,0.002398727,0.0008895861,0.001476162,0.002794757,0.003520441,0.01622221],"category_scores_gemma":[0.003727833,0.0004506963,0.001640477,0.004033081,0.0005616353,0.00101845,0.001145936,0.001781922,0.01618336],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001685027,"about_ca_system_score_gemma":0.002244805,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05044276,"about_ca_topic_score_gemma":0.0871695,"domain_scores_codex":[0.9988647,0.0001709438,0.0001027446,0.0003152909,0.0003264286,0.0002199549],"domain_scores_gemma":[0.9984534,0.000442756,0.00009170941,0.0003990999,0.0004215347,0.0001913624],"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":[0.0003046329,0.0002347302,0.003629489,0.0006528512,0.00008598441,0.0002723705,0.00004420678,0.004882749,0.0004640301,0.0007101899,0.9814123,0.007306466],"study_design_scores_gemma":[0.001110481,0.0002820161,0.03542115,0.0005191026,0.0001972432,0.001174575,0.001018349,0.02910038,0.003628702,0.003612296,0.9237659,0.000169839],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.007450562,0.0003060826,0.0002637837,0.0004264926,0.0001415296,0.00004448927,0.9880323,0.0008700468,0.002464711],"genre_scores_gemma":[0.005919353,0.0000897807,0.0008252324,0.0001016793,0.00001490855,0.00005336046,0.9918522,0.00004850562,0.001095007],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.05044276,"threshold_uncertainty_score":0.1002983,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06483507960166793,"score_gpt":0.330095768978752,"score_spread":0.265260689377084,"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."}}