{"id":"W4367400073","doi":"10.1016/j.conbuildmat.2023.131419","title":"A review of microstructure characterization of asphalt mixtures using computed tomography imaging: Prospects for properties and phase determination","year":2023,"lang":"en","type":"review","venue":"Construction and Building Materials","topic":"Asphalt Pavement Performance Evaluation","field":"Engineering","cited_by":97,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Materials science; Asphalt; Tortuosity; Void (composites); Composite material; Characterization (materials science); Compaction; Anisotropy; Tomography; Porosity; Microstructure; Optics","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":[0.0009573774,0.001370567,0.001757163,0.003743322,0.0002304599,0.001069511,0.0009878192,0.001083723,0.00215795],"category_scores_gemma":[0.001096813,0.0005507672,0.0006162754,0.004053335,0.0004625859,0.00166907,0.0006073826,0.001048764,0.001203584],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004917924,"about_ca_system_score_gemma":0.001450662,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002020321,"about_ca_topic_score_gemma":0.003432635,"domain_scores_codex":[0.9997051,0.00003254301,0.00004841695,0.00007219596,0.0001200106,0.00002169764],"domain_scores_gemma":[0.9992563,0.0003142232,0.0001221397,0.00002033699,0.000251784,0.00003522385],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00007534481,0.0001238554,0.0003720377,0.04007533,0.000136274,0.0001460918,0.0000518066,0.000771304,0.01092852,0.002430558,0.01699789,0.927891],"study_design_scores_gemma":[0.00002054465,0.0002874597,0.002314231,0.007070996,0.0004784258,0.001266189,0.0001244351,0.0005097773,0.007099294,0.001771197,0.9789649,0.0000926623],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.000222203,0.9987311,0.0003643695,0.00008465568,0.00009816036,0.000005918162,0.00004355138,0.000007261512,0.0004428067],"genre_scores_gemma":[0.0008123498,0.9980047,0.000622838,0.0000886417,0.0001008515,0.000007070256,0.00005762357,0.000002077649,0.0003038167],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.003743322,"threshold_uncertainty_score":0.007219076,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05650895808282367,"score_gpt":0.3265088914569917,"score_spread":0.2699999333741681,"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."}}