{"id":"W4233717635","doi":"10.1111/j.1708-8208.2013.0012044.x","title":"Reviewer Acknowledgment","year":2013,"lang":"en","type":"article","venue":"Clinical Implant Dentistry and Related Research","topic":"Legal and Policy Issues","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Citation; Library science; Psychology; Computer science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.004231248,0.00007950942,0.0002069487,0.00005709385,0.0007824735,0.0002348067,0.0002820174,0.0003338012,0.003093786],"category_scores_gemma":[0.004082393,0.00005713007,0.00008804718,0.0003129425,0.001138875,0.0001847279,0.0001621237,0.0008903633,0.01128983],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001950609,"about_ca_system_score_gemma":0.0001219311,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001169136,"about_ca_topic_score_gemma":0.00011888,"domain_scores_codex":[0.9969926,0.001292768,0.0004349551,0.0002817261,0.0004522793,0.0005456315],"domain_scores_gemma":[0.9974856,0.001174577,0.00004879128,0.0001916571,0.0006295752,0.0004697504],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000008604735,0.0001695671,0.003033477,0.00006142223,0.00007899283,0.0007181015,0.001519072,4.284807e-8,0.00004667797,0.01309548,0.9144149,0.06685364],"study_design_scores_gemma":[0.0002639137,0.00007648866,0.006569781,0.0001179553,0.00001191807,0.0001980175,0.0005971041,0.000008208173,0.00002270613,0.008261719,0.9837595,0.000112746],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.818817,0.006874537,0.000002017943,0.01346825,0.01413617,0.0008267229,0.00001184564,0.00009862991,0.1457649],"genre_scores_gemma":[0.8098011,0.01647894,0.00002925995,0.0001880598,0.001263881,0.00003185288,0.000008966683,0.000009044354,0.1721889],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06934452,"threshold_uncertainty_score":0.9978175,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2563371212545695,"score_gpt":0.5580231378625129,"score_spread":0.3016860166079434,"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."}}