{"id":"W3088730365","doi":"10.1119/10.0002064","title":"Smartphones and Gravitational Acceleration II: Applications","year":2020,"lang":"en","type":"article","venue":"The Physics Teacher","topic":"Geophysics and Gravity Measurements","field":"Earth and Planetary Sciences","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Accelerometer; Acceleration; Gravimeter; Gravitational acceleration; Exploit; Computer science; Software; Purchasing; Mobile device; Gravitation; Human–computer interaction; Simulation; Computer security; Engineering; Physics; World Wide Web; Operating system; Astronomy; Mechanical engineering","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":[0.0004713606,0.001315435,0.0003960821,0.0006773963,0.0003903068,0.001553581,0.000647585,0.001135,0.03938065],"category_scores_gemma":[0.00198992,0.0003657624,0.0003440747,0.0007933847,0.0001945267,0.001553539,0.001796531,0.0007484187,0.02865033],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002666044,"about_ca_system_score_gemma":0.0003298275,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000710209,"about_ca_topic_score_gemma":0.001080228,"domain_scores_codex":[0.9995564,0.00007547737,0.00003669231,0.0000681126,0.0001987443,0.00006457141],"domain_scores_gemma":[0.9994067,0.0001775486,0.0000360737,0.00007570727,0.0001800511,0.0001239417],"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":[0.0002085677,0.0002380035,0.001464912,0.0009823871,0.00001193332,0.0003351092,0.0009157352,0.001132331,0.01437404,0.00644033,0.3267097,0.647187],"study_design_scores_gemma":[0.00005477893,0.0003029792,0.006491219,0.0006229957,0.00001872875,0.001224159,0.000442203,0.002448941,0.005078077,0.005039395,0.9782236,0.00005292047],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.06729051,0.03070621,0.2572205,0.01062368,0.004201543,0.003207944,0.008064281,0.05354952,0.5651358],"genre_scores_gemma":[0.2623359,0.03256088,0.1891715,0.008107081,0.003549123,0.003276057,0.009723864,0.005885163,0.4853904],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03938065,"threshold_uncertainty_score":0.1317413,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0496436910252992,"score_gpt":0.2301230372473984,"score_spread":0.1804793462220992,"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."}}