Bibliographic record
Abstract
What's Changed Fix (and test) the pgi tutorials. by @jcapriot in https://github.com/simpeg/simpeg/pull/1133 Run style checks in Azure Pipelines by @santisoler in https://github.com/simpeg/simpeg/pull/1134 Add property to control number of processes created. by @jcapriot in https://github.com/simpeg/simpeg/pull/1135 Use r-strings on strings and docstrings that contain backslashes by @santisoler in https://github.com/simpeg/simpeg/pull/1136 Run flake8 in CI against a selection of rules by @santisoler in https://github.com/simpeg/simpeg/pull/1141 Rename variables to avoid shadowing builtins by @santisoler in https://github.com/simpeg/simpeg/pull/1137 Ignore flake warning over empty docstrings by @santisoler in https://github.com/simpeg/simpeg/pull/1149 Avoid using getattr with fixed constant strings by @santisoler in https://github.com/simpeg/simpeg/pull/1139 Separate flake 8 ignores by line breaks by @jcapriot in https://github.com/simpeg/simpeg/pull/1150 Avoid using mutables as default parameters by @santisoler in https://github.com/simpeg/simpeg/pull/1142 Ignore b028 by @jcapriot in https://github.com/simpeg/simpeg/pull/1155 Remove unused imports across SimPEG by @santisoler in https://github.com/simpeg/simpeg/pull/1132 Avoid calling functions in default arguments by @santisoler in https://github.com/simpeg/simpeg/pull/1143 Fix plot_inv_mag_MVI_Sparse_TreeMesh.py by @thibaut-kobold in https://github.com/simpeg/simpeg/pull/1159 fix mref depreciation in regularization/pgi.py by @thibaut-kobold in https://github.com/simpeg/simpeg/pull/1157 Avoid using variables not binded in function definition by @santisoler in https://github.com/simpeg/simpeg/pull/1145 Remove unused loop variables by @santisoler in https://github.com/simpeg/simpeg/pull/1138 Enable use of inactive cells in equivalent source models by @nwilliams-kobold in https://github.com/simpeg/simpeg/pull/1147 Flexible dc boundary by @jcapriot in https://github.com/simpeg/simpeg/pull/1168 Do not use multiprocessing on single thread. by @jcapriot in https://github.com/simpeg/simpeg/pull/1170 fix gmm.plot_pdf new error from sklearn >=1.2 by @thibaut-kobold in https://github.com/simpeg/simpeg/pull/1156 Black 23.1 by @jcapriot in https://github.com/simpeg/simpeg/pull/1174 Fix for _has_fields by @jcapriot in https://github.com/simpeg/simpeg/pull/1175 Do not import deprecated discretize utilities by @jcapriot in https://github.com/simpeg/simpeg/pull/1176 update codecov script by @jcapriot in https://github.com/simpeg/simpeg/pull/1178 Linear mapping by @jcapriot in https://github.com/simpeg/simpeg/pull/1177 Use discretize.utils.active_from_xyz to get active topography cells by @dccowan in https://github.com/simpeg/simpeg/pull/1171 Update minimum versions by @jcapriot in https://github.com/simpeg/simpeg/pull/1179 Add B028 to flake8 ignore by @jcapriot in https://github.com/simpeg/simpeg/pull/1181 Add possibility to pass fields to getJtJdiag by @jcapriot in https://github.com/simpeg/simpeg/pull/1182 Mira review beta estimator by @dccowan in https://github.com/simpeg/simpeg/pull/1173 Add option for amplitude threshold on UpdateSens directive by @domfournier in https://github.com/simpeg/simpeg/pull/1163 Change default n_processes for potential fields by @jcapriot in https://github.com/simpeg/simpeg/pull/1186 Update current_utils.py by @domfournier in https://github.com/simpeg/simpeg/pull/1166 Avoid comparing bool variables to True or False by @santisoler in https://github.com/simpeg/simpeg/pull/1160 Avoid using bare excepts that catch every possible exception by @santisoler in https://github.com/simpeg/simpeg/pull/1140 Update SimPEG.Report() by @prisae in https://github.com/simpeg/simpeg/pull/1104 Addition regarding inversion to big_picture by @prisae in https://github.com/simpeg/simpeg/pull/729 Do not store real lambdas as complex by @jcapriot in https://github.com/simpeg/simpeg/pull/1190 Improve docstring of depth_weighting by @santisoler in https://github.com/simpeg/simpeg/pull/1192 Add issue forms for github by @jcapriot in https://github.com/simpeg/simpeg/pull/1189 Update deprecation usage in optimization module by @jcapriot in https://github.com/simpeg/simpeg/pull/1194 Update getting started guides by @jcapriot in https://github.com/simpeg/simpeg/pull/1188 Update DC1D for flexibility and speed by @jcapriot in https://github.com/simpeg/simpeg/pull/1191 Start removing unused variables by @santisoler in https://github.com/simpeg/simpeg/pull/1161 Fix check for reference_model in PGI regularization by @santisoler in https://github.com/simpeg/simpeg/pull/1196 update JTV to work for an arbitrary number of models by @jcapriot in https://github.com/simpeg/simpeg/pull/1197 Simulation of Simulations by @jcapriot in https://github.com/simpeg/simpeg/pull/1183 Remove flake errors that were already solved by @santisoler in https://github.com/simpeg/simpeg/pull/1203 Fix flake8 B015 errors: solve unused comparisons by @santisoler in https://github.com/simpeg/simpeg/pull/1200 Fix flake E401 error: multiple imports in one line by @santisoler in https://github.com/simpeg/simpeg/pull/1202 Patch/identity map init by @jcapriot in https://github.com/simpeg/simpeg/pull/1205 Fix length scale getters by @jcapriot in https://github.com/simpeg/simpeg/pull/1207 Patch/fix save sparse dict by @jcapriot in https://github.com/simpeg/simpeg/pull/1206 Add PR template file by @jcapriot in https://github.com/simpeg/simpeg/pull/1208 0.19.0 Staging by @jcapriot in https://github.com/simpeg/simpeg/pull/1209 Full Changelog: https://github.com/simpeg/simpeg/compare/v0.18.1...v0.19.0
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.004 | 0.003 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.006 | 0.006 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.306 | 0.334 |
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".