{"id":"W4247957655","doi":"10.29303/spektrum.v6i1.148","title":"ANALISIS MODULUS GESER MAKSIMUM TANAH LEMPUNG EKSPANSIF DENGAN PERKUATAN SERAT IJUK BERDASARKAN METODE EMPIRIS","year":2020,"lang":"ms","type":"article","venue":"Spektrum Sipil","topic":"Geotechnical and construction materials studies","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Kootenay Association for Science & Technology","funders":"","keywords":"Physics","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":[0.002943489,0.001127217,0.001370278,0.002206628,0.0008140125,0.002849769,0.0009002339,0.001224853,0.01128296],"category_scores_gemma":[0.004647595,0.0006264111,0.001503668,0.002254061,0.0008444851,0.001817275,0.0009514141,0.001605408,0.003300714],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001209709,"about_ca_system_score_gemma":0.001472715,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005007647,"about_ca_topic_score_gemma":0.006500228,"domain_scores_codex":[0.9980184,0.0003826295,0.0001597057,0.0003481692,0.0009149369,0.0001762676],"domain_scores_gemma":[0.9968688,0.001551038,0.0003444305,0.0001923463,0.0009529861,0.00009052413],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.003492326,0.001233504,0.2408605,0.009814867,0.001049699,0.003072463,0.006491233,0.02230472,0.2642418,0.008084746,0.01093228,0.4284219],"study_design_scores_gemma":[0.0001519552,0.00495988,0.3955241,0.002505148,0.001684417,0.004829024,0.01983578,0.0523173,0.3761147,0.009124798,0.1324384,0.0005144577],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8758439,0.0269431,0.05193612,0.001455087,0.0004899668,0.0006619793,0.004891799,0.0004980682,0.03728001],"genre_scores_gemma":[0.9399012,0.01017374,0.02487279,0.0003665513,0.00009257706,0.0005395766,0.002155148,0.0002482556,0.02165018],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01128296,"threshold_uncertainty_score":0.03774524,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02769268878231803,"score_gpt":0.1920811469948074,"score_spread":0.1643884582124893,"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."}}