{"id":"W2899503061","doi":"10.1051/matecconf/201819907002","title":"Characterization tools for shrinkage-compensating repair materials","year":2018,"lang":"en","type":"article","venue":"MATEC Web of Conferences","topic":"Concrete and Cement Materials Research","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke; Université Laval","funders":"","keywords":"Shrinkage; Expansive; Cracking; Compatibility (geochemistry); Portland cement; Computer science; Cement; Materials science; Composite material; Compressive strength","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002812931,0.0001048994,0.000214802,0.00007051895,0.00005011161,0.0001446143,0.000144459,0.00005396385,0.004605818],"category_scores_gemma":[0.00005572011,0.00009606474,0.00003456332,0.00006403141,0.00005891578,0.000195618,0.00003399905,0.00002257763,0.00008018712],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000009509596,"about_ca_system_score_gemma":0.00007119382,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000148694,"about_ca_topic_score_gemma":0.000006016714,"domain_scores_codex":[0.9992131,0.00002426866,0.0003072413,0.000121592,0.0001295269,0.0002042712],"domain_scores_gemma":[0.9995673,0.00006383052,0.00005677161,0.0001457652,0.0001370327,0.00002926818],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00002508474,0.000003321274,0.0001343504,0.0002174584,0.00002524168,2.605891e-7,0.00006963631,0.000001202331,0.9931523,0.002026253,0.0001041378,0.004240721],"study_design_scores_gemma":[0.0002130144,0.0001189741,0.00226297,0.00006452543,0.000007803353,6.333317e-7,0.00005115983,0.002532205,0.9748159,0.0001168948,0.01969515,0.0001207821],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9891132,0.000009625312,0.0008118252,0.00002305961,0.0003474131,0.0003156627,0.0001119251,0.0002403295,0.009026946],"genre_scores_gemma":[0.9989522,0.00002832993,0.0003695749,0.00001025792,0.0002308086,0.00006911907,0.0001055665,0.00001624153,0.0002179347],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01959101,"threshold_uncertainty_score":0.9963041,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03748578810978655,"score_gpt":0.2708228201580257,"score_spread":0.2333370320482391,"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."}}