{"id":"W6940300424","doi":"10.7910/dvn/ktcbc1","title":"Replication Data for: Predictive Modeling of Concrete Stress-Strain Relationship Using P-LSTM","year":2024,"lang":"en","type":"dataset","venue":"Harvard Dataverse","topic":"Mycorrhizal Fungi and Plant Interactions","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Aggregate (composite); Workflow; Suite; Replication (statistics); Code (set theory); Set (abstract data type); Data set; Dimension (graph theory); Point (geometry)","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":[0.0009368003,0.002121449,0.0008905589,0.000803786,0.0005517735,0.001452785,0.004655543,0.002007858,0.1762096],"category_scores_gemma":[0.007451377,0.0007775898,0.001400966,0.001367664,0.0005898434,0.002024254,0.002024895,0.00264928,0.09761129],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008733673,"about_ca_system_score_gemma":0.001885143,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01525679,"about_ca_topic_score_gemma":0.02395377,"domain_scores_codex":[0.9993191,0.00008865413,0.00005903346,0.0001774528,0.000296,0.00005976739],"domain_scores_gemma":[0.997799,0.000559554,0.00007230171,0.0007034288,0.000781365,0.00008429396],"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":[0.0002449913,0.0001116409,0.001306258,0.0008003603,0.00005975979,0.0001947092,0.00006081224,0.02576369,0.002480702,0.00317457,0.918291,0.04751134],"study_design_scores_gemma":[0.0008916692,0.0002291995,0.003567988,0.0004449575,0.00006025188,0.0002767057,0.0001577515,0.2783075,0.02954454,0.02450804,0.6618077,0.0002037927],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.006413661,0.0005050415,0.08102544,0.001683352,0.00205855,0.0004704403,0.7690767,0.1197974,0.01896936],"genre_scores_gemma":[0.03646176,0.0004682882,0.08200912,0.0006821237,0.0001367863,0.001226527,0.8449023,0.01567009,0.01844294],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1762096,"threshold_uncertainty_score":0.5894797,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08211876999533134,"score_gpt":0.2923930145159416,"score_spread":0.2102742445206102,"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."}}