Bibliographic record
Abstract
B.H. Baltagi: Introduction.- J.H. Abbring, G.J. van den Berg: Analyzing the effect of dynamically assigned treatments using duration models, binary treatment models, and panel data models.- W. Greene: Convenient estimators for the panel probit model: Further results.- P. Contoyannis, A.M. Jones, N. Rice: Simulation-based inference in dynamic panel probit models: An application to health.- S. Karlsson, J. Skoglund: Maximum-likelihood based inference in the two-way random effects model with serially correlated time effects.- M.J.G. Bun: Testing poolability in a system of dynamic regressions with nonspherical disturbances.- B.H. Baltagi, G. Bresson, A. Pirotte: Tobin q: Forecast performance for hierarchical Bayes, shrinkage, heterogeneous and homogeneous panel data estimators.- C. Driver, K. Imai, P. Temple, G. Urga: The effect of uncertainty on UK investment authorisation: Homogeneous vs. heterogeneous estimators.- D. Hum, W. Simpson: Reinterpreting the performance of immigrant wages from panel data.- M. Gillman, M. Harris, L. Matyas: Inflation and growth: Explaining a negative effect.- L. Orea, S. Kumbhakar: Efficiency measurement using a latent class stochastic frontier model.- S. Kumbhakar: Productivity and technical change: Measurement and testing.- R. Chakir, A. Bousquet, N. Ladoux: Modeling corner solutions with panel data: Application to the industrial energy demand in France.- F. Peracchi: The European Community Household Panel: A review.- T.J. Knieser, Qi Li: Nonlinearity in dynamic adjustment: Semiparametric estimation of panel labor supply.- K. Hadri, C. Guermat, J. Whittaker: Estimation of technical inefficiency effects using panel data and doubly heteroscedastic stochastic production frontiers.- P. Egger, M. Pfaffermayr: The proper panel econometric specification of the gravity equation: A three-way model with bilateral interaction effects.- D. Parent: Employer-supported training in Canada and its impact on mobility and wages.- Ho Tsung-wu: A panel cointegration approach to the investment-saving correlation.- A. Aakvik: Estimating the employment effects of education for disabled workers in Norway.- B. Fitzenberger, C. Kurz: New insights on earnings trends across skill groups and industries in West Germany.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.010 | 0.033 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.004 | 0.012 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.029 | 0.009 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".