{"id":"W3202649081","doi":"10.15278/isms.2021.fi13","title":"TUNNELING DYNAMICS IN &lt;span class=\"roman\"&gt;N&lt;/span&gt;&lt;sub&gt;&lt;span class=\"roman\"&gt;2&lt;/span&gt;&lt;/sub&gt;&amp;#8722;&lt;span class=\"roman\"&gt;D&lt;/span&gt;&lt;sub&gt;&lt;span class=\"roman\"&gt;2&lt;/span&gt;&lt;/sub&gt;&lt;span class=\"roman\"&gt;O&lt;/span&gt; OBSERVED IN THE &lt;span class=\"roman\"&gt;OD&lt;/span&gt; STRETCHING REGION","year":2021,"lang":"en","type":"article","venue":"Proceedings of the 2021 International Symposium on Molecular Spectroscopy","topic":"Molecular Spectroscopy and Structure","field":"Chemistry","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Span (engineering); Life span; Quantum tunnelling; Class (philosophy); Physics; Computer science; Engineering; Gerontology; Quantum mechanics; Structural engineering; Medicine; Artificial intelligence","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":["metaresearch","metaepi_narrow","metaepi_broad","bibliometrics","sts","scholarly_communication","open_science","research_integrity","insufficient_payload"],"consensus_categories":["metaepi_narrow","metaepi_broad","sts","open_science","research_integrity","insufficient_payload"],"category_scores_codex":[0.01341481,0.0243892,0.02182783,0.01161806,0.009429037,0.01324804,0.03497913,0.01686041,0.005143909],"category_scores_gemma":[0.008778467,0.02570339,0.01552996,0.01915831,0.008420097,0.01045943,0.01607251,0.02519451,0.002708652],"about_ca_system_candidate":true,"about_ca_system_consensus":true,"about_ca_system_score_codex":0.02630286,"about_ca_system_score_gemma":0.008183812,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009186466,"about_ca_topic_score_gemma":0.02040861,"domain_scores_codex":[0.8925748,0.006650366,0.02348753,0.02643322,0.02760087,0.02325314],"domain_scores_gemma":[0.933919,0.00532863,0.02100365,0.01914621,0.01065342,0.009949164],"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":[0.008885358,0.009903193,0.005763846,0.004727311,0.01048034,0.005036884,0.005486582,0.009553369,0.8088272,0.06365315,0.06550536,0.002177467],"study_design_scores_gemma":[0.039956,0.006966295,0.01337934,0.0173258,0.01217078,0.006531309,0.004058325,0.102127,0.453702,0.01379383,0.2962902,0.0336991],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8391569,0.01724144,0.005248106,0.02473772,0.01566032,0.01731228,0.00747826,0.006283447,0.06688156],"genre_scores_gemma":[0.9063353,0.02070235,0.01108928,0.005725026,0.01150764,0.005898443,0.01406612,0.008016081,0.01665975],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3551251,"threshold_uncertainty_score":0.9995844,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009980606807572795,"score_gpt":0.2380544281838626,"score_spread":0.2280738213762898,"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."}}